DEV Community: NocoBase

Weekly Updates : Add External Vector Store Configuration Form for AI Knowledge Bases

NocoBase — Sun, 21 Jun 2026 07:39:13 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260619

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated with three branches: main , next and develop.

main：The most stable version to date, recommended for installation;
next：Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It's mainly for test users to collect feedback and optimize functions further. Ideal for test users who want to experience new features early and give feedback;
develop：Alpha version, contains the latest feature code, may be incomplete or unstable, mainly for internal dev and rapid iteration. Suited for tech users interested in product's cutting-edge, but with potential issues and incomplete functions. Not for production use.

main

🚀 Improvements

[client-v2] Add override value option for field value settings. (#9578) by gchust

🐛 Bug Fixes

[client-v2]
- Fixed custom action workflow trigger buttons sending custom context JSON under an extra values property or as a serialized string. (#9815) by mytharcher
- Fixed an issue where configuring an association field value as a fixed value or default value would not take effect. (#9820) by gchust
[auth] Encrypted password data is no longer included in sign-in status responses (#9836) by 2013xile
[app] Ignore unrelated currentScript when inferring plugin public path (#9839) by chenos
[UI templates] Fixed incorrect default context for ctx.openview. (#9811) by gchust

🐛 Bug Fixes

[ai]
- Locked @langchain/openai to patch-level updates for AI packages. (#9829) by cgyrock
- Fixed incompatible LangChain dependency resolution for AI plugins. (#9831) by cgyrock
[AI: Knowledge base]
- Fixed unclear error messages when enabling the AI knowledge base plugin without the AI plugin available. by cgyrock
- Fixed incompatible LangChain dependency resolution for the AI knowledge base plugin. by cgyrock

🎉 New Features

[Backup manager] Support backup and restore for KingBase as the primary database (#9791) by 2013xile
[Migration manager] Support migrations for KingBase as the primary database. by 2013xile

🚀 Improvements

[AI: Knowledge base] Improved AI knowledge base retrieval and documentation. (#9765) by cgyrock
[cli] Add env config schema version (#9782) by chenos
[Workflow] Stabilize update options test (#9773) by mytharcher
[File manager] Improved PDF previews: cross-origin PDF files now use the browser-native viewer, while same-origin PDF files continue to use PDF.js. (#9796) by mytharcher
[Backup manager] Tables whose collection dataCategory is marked as 'runtime' are now automatically excluded from backups. (#9804) by cgyrock
[AI: Knowledge base] Improved AI knowledge base document segmentation, segment management, hit tests, and document workflow node support. by cgyrock

🐛 Bug Fixes

[client-v2]
- Fixed an issue where form submission would show an incorrect message when a subform contained a sub-table. (#9807) by gchust
- Fixed an issue where event flows on sub-table columns would execute incorrectly. (#9821) by gchust
- Removed unexpected updateAssociationValues from association fields (#9812) by katherinehhh
- Fixed untranslated Yes/No options in v2 filter form checkbox dropdowns. (#9792) by katherinehhh
- Fixed the issue where event flow settings could not be updated after saving a block as a template. (#9585) by gchust
- Fixed incorrect display and format settings when v2 table association title fields use time, date-only, or datetime fields. (#9785) by katherinehhh
[Workflow] Fixed workflow dispatcher recovery after unexpected dispatch errors. (#9783) by mytharcher
[File manager] Fixed 404 errors when uploading files to attachment URL fields in external data sources (#9809) by 2013xile
[Action: Custom request] Fixed V2 custom request actions showing an unnecessary error when request settings are not configured. (#9802) by katherinehhh
[AI employees]
- Fixed an issue where AI employees could not correctly fill sub-table data. (#9801) by gchust
- Fixed AI employee shortcut task triggers so that attachments from the current work context are included when running a task from the shortcut profile. (#9808) by cgyrock
[Workflow: Custom action event] Fixed action panel v2 trigger workflow buttons showing success and sending a request when no workflow is bound. (#9798) by mytharcher
[Flow engine] Fixed an issue where current record forms and details in popup could contain incorrect data when built by AI. (#9788) by gchust
[Async task manager] Fixed async task file download errors when the task id is missing from filterByTk. (#9705) by mytharcher
[Data source: External NocoBase] Proxy NocoBase external data source file upload and storage actions by upload data source by 2013xile
[Multi-space] Fixed permission errors when space managers add users without access to the user email field. by jiannx
[Workflow: Subflow] Fixed asynchronous subflows so that parent workflows can resume after worker restart or in-memory event mapping loss. by mytharcher
[App supervisor] Fixed a crash when remote WebSocket proxy responses fail by 2013xile

🎉 New Features

[Workflow: Mailer node] Added support for sending attachments in workflow mailer nodes. (#9724) by mytharcher

🚀 Improvements

[client-v2] Relation field column data scopes in form subtables now support current item variables. (#9444) by gchust
[undefined] Unified the Chinese documentation name of the version control plugin as “版本控制”. (#9776) by cgyrock
[File manager] Added selectable text support to PDF previews in the file manager for PDFs with embedded text. (#9781) by mytharcher
[Action: Bulk edit] Optimized the loading method for v2 action plugins and kept the order of migrated action buttons stable. (#9778) by katherinehhh
[Version control] Changed the Chinese display name of the version control plugin to “版本控制”. by cgyrock

🐛 Bug Fixes

[cli-v1] Fixed an error when running yarn dev after upgrading projects created with create-nocobase-app from 2.0 to 2.1. (#9775) by Molunerfinn
[client-v2] Fixed the issue where migration progress did not show the dedicated progress view. (#9761) by 2013xile
[flow-engine] Fixed Vietnamese and Chinese IME input issues in v2 single-line text and multiline text fields. (#9764) by katherinehhh
[server] Fixed unsafe plugin name handling in pm:enable to prevent local file inclusion risks during plugin resolution. (#9701) by mytharcher
[File manager] Fixed PDF preview failures caused by abnormal pdf.js worker module loading. (#9779) by mytharcher
[Block: Kanban] Fixed the issue where opening Calendar, Gantt, and Kanban blocks outside edit mode unexpectedly persisted hidden popup actions and repeatedly sent delete requests. (#9772) by jiannx
[Action: Export records Pro] Improved processing mode settings and explanatory prompts for v2 Import/Export Pro. by katherinehhh
[Migration manager] Fixed possible failures when importing large migration data files. by 2013xile
[Template print] Rejected unsupported template file types before template printing starts. by 2013xile

🚀 Improvements

[Workflow] Improved the workflow metadata editing experience by supporting description editing in the details popup and automatically filling source workflow metadata when duplicating workflows. (#9766) by mytharcher

🐛 Bug Fixes

[Action: Import records] Changed uploaded import files to disk storage to reduce memory pressure during large data imports. (#9739) by mytharcher
[Backup manager] Fixed a security issue where unsafe PostgreSQL schema names could be accepted during backup restoration. (#9758) by 2013xile
[Workflow]
- Fixed workflow timeout handling so aborted executions and their pending tasks can be updated atomically. (#9768) by mytharcher
- Fixed the issue where the workflow’s last updated by field was not updated after workflow node changes. (#9769) by mytharcher
[Action: Import records Pro] Avoided parsing large files in the request node before Pro import creates an async task. by mytharcher
[Version control] Adjusted the position of the version control top shortcut entry so it appears next to the UI editor in both legacy and v2 admin layouts. by cgyrock

🚀 Improvements

[cli]
- normalize app compat build versions (#9763) by chenos
- support updating skills to a specified version (#9760) by chenos

🐛 Bug Fixes

[client] Fixed the issue where fields in horizontal subforms are too narrow to display data (#9755) by zhangzhonghe
[Data source manager]
- Fixed the blank edit field drawer caused by repeated rerenders on the v1 external data source Configure fields page. (#9759) by katherinehhh
- Fixed an issue where deleting the active collection category in the v1 data source manager could leave the All collections tab empty. (#9757) by katherinehhh
[Async task manager] Fixed incorrect request IDs in async task worker logs (#9686) by 2013xile
[Workflow: SQL node] Fixed SQL workflow legacy template-variable migration being skipped for some beta-version users. (#9762) by mytharcher
[AI employees]
- Fixed loss of message configuration in workflow LLM nodes. (#9743) by cgyrock
- Fixed an issue where attachments pasted into the AI employee dialog could not be removed. (#9753) by cgyrock
[Block: Kanban] Fixed URL support for calendar and related popups. (#9751) by jiannx
[Workflow: Approval] Fixed the issue where related data is not displayed in v2 approval forms by zhangzhonghe

🎉 New Features

[AI employees] Added an external vector store configuration form for AI knowledge bases. (#9723) by cgyrock
[AI: Knowledge base] Added an external vector store configuration form for AI knowledge bases. by cgyrock

🚀 Improvements

[undefined]
- Added a version control scenario to the AI builder quick start (#9748) by Molunerfinn Reference: AI Builder Quick Start
- Improved the version control documentation with AI Builder automatic revision guidance. (#9745) by cgyrock
[cli] clarify init setup wording (#9750) by chenos
[Action: Import records] Improved import and async task error dialogs so long error messages can be fully read without breaking the layout. (#9746) by katherinehhh
[Action: Import records Pro] Improved import dialogs so long error messages remain readable and v2 processing mode can be selected directly from the settings menu. by katherinehhh

🐛 Bug Fixes

[client-v2] Fixed the issue where v2 pages could keep loading after signing in (#9738) by zhangzhonghe
[cli] require Node.js 22 for nb (#9749) by chenos
[File manager] Fix PDF previews missing CJK/CID font text after switching to pdf.js. (#9737) by mytharcher

🚀 Improvements

[cli] Added schema version records for env configuration. (#9782) by chenos
[File manager] Improved PDF previews: cross-origin PDF files now use the browser-native preview, while same-origin PDF files continue to be rendered with PDF.js. (#9796) by mytharcher

🐛 Bug Fixes

[client-v2]
- Fixed the issue where event flow settings could no longer be modified after a block was converted into a template. (#9585) by gchust
- Fixed the issue where checkbox dropdown options in v2 filter forms did not display translated text. (#9792) by katherinehhh
- Fixed incorrect display and format settings when the title field of a v2 table relation field used a time, date, or datetime field. (#9785) by katherinehhh
[Flow engine] Fixed incorrect data in current record forms and detail data inside popups during AI building. (#9788) by gchust
[Workflow: Custom action event] Fixed the issue where action panel v2 trigger workflow buttons still showed success and sent requests when no workflow was bound. (#9798) by mytharcher
[AI employees] Fixed the issue where AI employees could not correctly fill sub-table data. (#9801) by gchust

🎉 New Features

[Workflow: Mailer node] Added support for sending attachments in workflow mailer nodes. (#9724) by mytharcher
[Workflow] Added support for database transaction scopes in workflows. (#9742) by mytharcher Reference: Database transactions
[Workflow: Database transaction node] Added a database transaction workflow node plugin. by mytharcher

🚀 Improvements

[client-v2] Relation field columns in form subtables now support current item variables in data scopes. (#9444) by gchust
[undefined] Unified the Chinese documentation name of the Version control plugin as “版本控制”. (#9776) by cgyrock
[File manager] Added selectable text support to PDF previews in File manager for PDFs with embedded text. (#9781) by mytharcher
[Users] Improved the layout of the v2 Users and Permissions pages and optimized department tree behavior. (#9780) by jiannx
[Action: Bulk edit] Optimized how v2 action plugins are loaded and kept the order of migrated action buttons stable. (#9778) by katherinehhh
[Version control] Renamed the Chinese display name of the Version control plugin to “版本控制”. by cgyrock

🐛 Bug Fixes

[cli-v1] Fixed an error when running yarn dev after upgrading projects created with create-nocobase-app from 2.0 to 2.1. (#9775) by Molunerfinn
[flow-engine] Fixed Vietnamese and Chinese IME input issues in v2 single-line text and multiline text fields. (#9764) by katherinehhh
[client-v2] Fixed the issue where migration progress did not display the dedicated progress view. (#9761) by 2013xile
[server] Fixed unsafe plugin name handling in pm:enable to avoid local file inclusion risks during plugin resolution. (#9701) by mytharcher
[Async task manager] Fixed database query errors caused by missing filterByTk when downloading async task files. (#9705) by mytharcher
[File manager] Fixed PDF preview failures caused by abnormal loading of the pdf.js worker module. (#9779) by mytharcher
[Block: Kanban] Fixed the issue where opening Calendar, Gantt, and Kanban blocks in non-edit mode unexpectedly persisted hidden popup actions and repeatedly sent delete requests. (#9772) by jiannx
[Action: Export records Pro] Improved the processing mode settings and help text for v2 Import/Export Pro. by katherinehhh
[Multi-space] Fixed the issue where space administrators could not add space users when they did not have permission for the user email field. by jiannx
[Migration manager] Fixed possible failures when importing large migration data files. by 2013xile
[Template print] Rejected unsupported template file types before template printing starts. by 2013xile

🎉 New Features

[AI employees] Added an external vector store configuration form for AI knowledge bases. (#9723) by cgyrock
[AI: Knowledge base] Added an external vector store configuration form for AI knowledge bases. by cgyrock
[Email manager] Migrated the Email manager client to v2. by jiannx

🚀 Improvements

[cli]
- Optimized compatibility checks for different version number formats. (#9763) by chenos
- Added support for updating skills to a specified version. (#9760) by chenos
- Improved the wording of initialization setup prompts. (#9750) by chenos
[undefined]
- Added a version control conversation scenario to the AI Builder overview page. (#9748) by Molunerfinn Reference: AI Builder Quick Start
- Improved version control documentation with notes on automatic version saving in AI Builder. (#9745) by cgyrock Reference: Version control
[Workflow] Improved the workflow metadata editing experience by supporting description editing in the details popup and automatically filling source workflow metadata when duplicating workflows. (#9766) by mytharcher
[Action: Import records] Improved import and async task error detail dialogs so long error messages can be fully viewed without breaking the layout. (#9746) by katherinehhh
[Translation test tool] Added a client-v2 settings page for the translation test tool. (#9744) by jiannx
[Action: Import records Pro] Improved import dialogs so long error messages can be fully viewed, and processing mode can be selected directly from the v2 settings menu. by katherinehhh

🐛 Bug Fixes

[client] Fixed the issue where fields in horizontal subforms were too narrow to display data. (#9755) by zhangzhonghe
[client-v2] Fixed the issue where v2 pages could keep loading after signing in. (#9738) by zhangzhonghe
[cli] Added Node.js version detection for the nb runtime environment. (#9749) by chenos
[Action: Import records] Changed uploaded import files to disk storage to reduce memory pressure during large data imports. (#9739) by mytharcher
[Async task manager] Fixed incorrect request IDs in async task worker logs. (#9686) by 2013xile
[Workflow]
- Fixed workflow timeout handling so aborted executions and their pending tasks can be updated atomically. (#9768) by mytharcher
- Fixed the issue where the workflow’s last updated by field was not updated after workflow node changes. (#9769) by mytharcher
[Data source manager]
- Fixed the blank field edit drawer caused by repeated rerenders on the v1 external data source Configure fields page. (#9759) by katherinehhh
- Fixed the issue where deleting the current collection category in the v1 data source manager could leave the All collections tab empty. (#9757) by katherinehhh
[Backup manager] Fixed a security issue where unsafe PostgreSQL schema names could be accepted during backup restoration. (#9758) by 2013xile
[Workflow: SQL node] Fixed the issue where SQL workflow legacy template variable migration was skipped for some beta-version users. (#9762) by mytharcher
[Block: Kanban] Fixed URL support for Calendar and other popups. (#9751) by jiannx
[AI employees]
- Fixed the issue where attachments pasted into the AI employee dialog could not be removed. (#9753) by cgyrock
- Fixed loss of message configuration in workflow LLM nodes. (#9743) by cgyrock
[File manager] Fixed missing Chinese/CID font text in some PDF previews after switching to pdf.js. (#9737) by mytharcher
[API documentation] Fixed the build failure of the API documentation plugin declaration file. (#9752) by katherinehhh
[Action: Import records Pro] Avoided parsing large files in the request node before Pro import creates an async task. by mytharcher
[Version control] Adjusted the position of the version control top shortcut entry so it appears next to the UI editor in both legacy and v2 admin layouts. by cgyrock
[Workflow: Approval] Fixed the issue where related data was not displayed in v2 approval forms. by zhangzhonghe

Do Software and Programmers Still Have a Future?

NocoBase — Tue, 16 Jun 2026 03:54:47 +0000

Originally published at https://www.nocobase.com/en/blog/future-of-software-programmers-revenue-doubled

Background

Six months ago, when we released NocoBase 2.0, we published our second recap: No AI, No VC, Just 17K Stars and Real Revenue. At that point, NocoBase had already reached around $1.4 million in annual revenue.

The plan had been simple: one recap a year, sharing NocoBase's growth as it happened. This third piece was supposed to wait until the end of this year, when NocoBase 3.0 comes out. But the world is changing too fast. AI is hitting this industry with a new shock wave almost every day. In a jolt like this, NocoBase was never going to remain untouched. We have been pulled, over and over, into all kinds of uncertainty.

So we had to move faster. We had to stay nimble enough to answer the shock as it came.

That is why this recap is arriving half a year early, together with NocoBase 2.1. Better to write it now than wait another six months and wonder whether this industry will still look the same by then. Or whether anyone will still care about an open-source product like this. Or whether anyone will still care about software, or programmers, at all.

Where We Are

It has now been five years since we committed the first line of code on GitHub.

Compared with six months ago, our team size has not changed. We are still 14 people. We still do not have a dedicated sales team. For the most part, users still find us, not the other way around. But beyond SEO, we have also started paying serious attention to generative engine optimization, and we already have quite a few paying users who discovered NocoBase through ChatGPT and Claude.

Here are a few other numbers:

GitHub stars: 22.7k
Contributors: 115
Git clones: 3K/day

Revenue

Now that the revenue figure is becoming more substantial, we will stop disclosing exact numbers in future recap articles. But we will keep sharing the trend lines, and the shape of what is happening underneath them.

In the first five months of 2026, our revenue was exactly double what it was in the same period of 2025. In our best month so far, monthly revenue alone had already reached our entire revenue for all of 2024.

But if I am being honest about how it felt from the inside, this was not the result of some smooth, graceful curve upward. It came after a major turn.

Were We About to Be Killed?

Before 2025, NocoBase was positioned as a no-code platform. It was a direction plenty of companies had already proven to be valuable and commercially viable, even if it was not the kind of business that usually leads to spectacular fortunes. The familiar products in this category can become solid businesses, even if they rarely produce outsized outcomes. With differentiated positioning, a standardized product, and a global market, we believed we had a chance to build a durable business around a focused product and a lean team.

Starting in 2025, we began introducing AI features into the product. That opened up a new imaginative horizon for the traditional no-code platform. AI could play a supporting role in business workflows and help people get certain kinds of work done more efficiently. At the same time, our revenue was climbing quickly, which seemed to validate the decision.

Then, at the end of 2025, things changed.

When Opus 4.5 was released, it felt as though the weather turned overnight. Social media was suddenly full of awe at the revolutionary changes it seemed to be bringing to programming. Then came the wave of layoff news, followed by all the loud voices declaring that traditional software was about to be killed. And just like that, the whole industry seemed to be living inside the same split reality, one half panic, one half exhilaration.

That mood spread through our team almost immediately.

More than one colleague started to feel that what we were building no longer had any meaning. And once that feeling takes hold, it does real damage. We had spent years building something we were proud of. Now AI appeared able to produce something similar in a few hours. And AI was still evolving at a frightening pace. So what were we still here for? Only a month earlier, I had believed that the stronger AI became, the better it would be for us, unless it planned to take over the entire world. Was that day really about to arrive this quickly?

At the same time, NocoBase's revenue also entered a weaker stretch. I could not tell whether that was just because of the Christmas and New Year holiday season, or because a flood of AI news had genuinely affected how enterprises were making purchasing decisions.

For two full months, I read obsessively. I tried product after product. Every day I discussed, argued, and compared notes with the more radical people on our team, while also trying to keep everyone grounded. I spoke with NocoBase users about how they viewed AI and how it was actually being used inside their companies.

And while I was doing all that, I sank into a serious state of anxiety, the kind I had not experienced in many years. When I was resting, I could hear my own heartbeat. I would fall asleep, wake up quickly, and find it hard to sleep again. The muscles in my abdomen were often so tight that I could feel them beating with my pulse.

NocoBase has not made us a huge amount of money. But everyone on this team has tied some part of their ideals to it, along with some part of their hope for a better life. If it were killed, it would hurt. A lot.

It was not until after February, after many rounds of intense discussion inside the team and many conversations with users, that I felt we had finally thought it through. We then held three all-hands alignment sessions in a row and shared a presentation called The Twilight of the Old Version, the Dawn of the New One. It laid out why NocoBase still deserves to exist, and where it should go next. We made sure everyone understood the reasoning behind the direction and felt confident moving forward.

Looking for What Does Not Change

The day before I started writing this piece, one of the three largest life sciences companies in the world contacted us. They wanted to explore using NocoBase as infrastructure, layering AI capabilities on top of traditional systems like SAP, and rebuilding certain parts of their supply chain on that basis.

For example, they want to identify and structure large volumes of orders arriving from different countries through fax, paper, handwriting, websites, and other channels. They want to plan shipping in batches based on warehouse locations and delivery destinations. They want to process accounts receivable, bills, and invoices more efficiently depending on different payment methods.

This is a giant enterprise with tens of thousands of employees spread across dozens of countries. They have no shortage of technical expertise and access to the most advanced models. So why would they still consider a product like NocoBase, instead of simply instructing an LLM to write the whole thing from scratch?

That was exactly the question we had been discussing and thinking through over the past few months.

Large models and agents are advancing at astonishing speed. They are making code itself incredibly cheap. They are making programmers as a group feel deeply uneasy. But once that same wave reaches traditional enterprises, it loses a lot of force.

The furniture company is still making furniture. The supply chain team is still doing supply chain work. Processes that never even made it to digitalization are still running on A4 paper and fax. These things are not going to undergo some revolutionary transformation just because LLMs can generate code. LLMs are not wish-granting machines. You cannot wave a magic wand and expect an entire enterprise to remake itself.

The bar is still very high. Solving real problems in production, sales, logistics, finance, and the rest of the business means building systems that are solid, secure, able to run for years, able to evolve, and able to absorb AI in ways that genuinely improve efficiency.

Code generation lowers the barrier to generating code. That is all. And in practice, if you use it badly, it may lead you straight into more traps.

In The Twilight of the Old Version, the Dawn of the New One, we listed several things that we believe will remain unchanged for quite a long time. Those are also the reasons we believe NocoBase still needs to exist.

If AI is going to truly land inside business, a chat window is not enough. AI needs a real operating environment. NocoBase gives it one, along with a ready-made toolbox. We turn data, workflows, and functional modules into interfaces AI can actually use, while surrounding that access with strict permissions and full logging. That is what allows AI to query data safely, identify risks, carry out complex tasks, and gradually move enterprise software from the old logic of "people looking for data" to a new logic of "tasks finding people."
An enterprise-grade system must have standardized data structures, rigorous permissions, strict business workflows, audit logs for every action, and historical records for key data. This layer is complex, and it cannot afford to be wrong. And no matter how much AI improves, it will not make these things disappear, because this is not really a problem of intelligence. It is a problem of people and organizations. Rather than asking AI to rewrite a fresh, half-proven version of this every time, it makes far more sense to build on top of standardized foundational modules that have already been thoroughly tested.
Enterprise applications contain a great deal of basic functionality that gets reused over and over again. User systems, authentication, email and SMS delivery, notification centers, data import and export, backend asynchronous jobs, almost every system needs them. As AI develops, these building blocks will keep changing too, and more AI-oriented tools will appear with them. But asking AI to rewrite them from scratch every single time is a massive waste. Reusing mature capabilities that already exist in the platform still creates enormous value.
WYSIWYG no-code visual configuration still matters. Its value is no longer just that it reduces the amount of code people need to write. It also gives AI output a visible surface that humans can adjust directly. If AI generates an interface or a workflow, people should be able to understand it at a glance, then refine it with their own hands. That kind of directness preserves transparency in human-AI collaboration. It keeps the system from turning into a black box that only AI understands and no one else can really move.
Without truly strong architectural design, the more code AI generates, the harder it becomes to maintain. NocoBase uses architecture to impose a set of physical rules on the system. It keeps interfaces and interaction styles highly consistent. It keeps automation under shared standards. It keeps plugins under shared standards too. That is what makes long-term, stable iteration possible.

Based on these things that do not change, we immediately adjusted our product positioning. We moved from "no-code platform" to "AI + no-code" infrastructure, and within a matter of weeks we completed the corresponding product changes. Of course, AI itself helped enormously, pushing our efficiency to more than twice what it was before. The no-code platform that had originally been built for people formally became a platform built for collaboration between people and AI.

And soon after that, we started receiving strong positive feedback from several large enterprises.

One pharmaceutical company, with more than 20,000 employees and dozens of subsidiaries, had begun promoting AI coding across the whole company months earlier. In the process, they had done a great deal of engineering work to deal with hallucinations, limited context windows, and architectural drift, all the problems that make long-term stable iteration so difficult. Even then, the results were not encouraging. Eventually, they concluded that a more sensible approach was to develop on top of a scaffold suited to AI, one that would preserve efficiency and flexibility while also placing strong constraints on AI behavior. After spending several weeks testing NocoBase, they concluded that NocoBase was exactly that kind of infrastructure.

Another top-tier renewable energy company in the wind power sector used NocoBase inside a single team for several months, then formally rolled it out across the entire company, to tens of thousands of employees, as an AI development platform. It has since gone into production in key scenarios such as review workflows, project management, and AI portals, allowing AI to create dependable value in those areas. They also have more than enough technical and business experts, the most advanced models, and essentially unlimited tokens. But spending time and resources on low-level infrastructure that does not generate returns is simply not worth it. Once they adopted NocoBase, they were able to focus most of their energy on the business itself.

What We Do Next

No matter what we think, AI is still moving very fast. If we want to stay alive for longer, and if we want to keep finding a sense of fulfillment true to our original intentions, then we need to keep reminding ourselves not to forget a few simple facts.

Stand on What Lasts

Under AI's impact, the pace of the world seems to have accelerated dramatically. And with social platforms, industry hype, and recommendation algorithms amplifying everything, we are bombarded by new concepts every day. But from what we have seen in real life, the world of AI vendors and online commentary is very different from the world of actual enterprises.

No matter how intense the conceptual bombardment becomes, real businesses are still making their pharmaceuticals, their cars, their bottled water. Many companies still have not even completed basic digitalization. They still rely heavily on paper and Excel, let alone any AI revolution. If we anchor ourselves in the things we can identify as lasting, and take those real businesses as the people we serve, that will be the foundation of our healthy survival.

Embrace What Changes Fast

Since the company was founded, we had been adding one or two new people to the product and engineering team every year. But starting this year, we decided to stop expanding the engineering team. Instead, we would give the existing team access to the most advanced models and plenty of tokens. In practice, the result is clear: people's output has already increased by at least a factor of two.

Using frontier models every day also keeps the team highly sensitive. It helps us really understand the boundaries of what these models can do, where they fit, and where they do not. Once we understand those things, we can fold them into NocoBase as part of the product itself.

Live in the Present

I have written so much above about "what lasts." But how long is "long-term," really? Six months? One year? Three years? To be honest, we ourselves cannot judge that with confidence.

But there is no need to let that become a source of anxiety. We are a bridge between AI and enterprises. AI is moving fast, so fast that it is hard to say what things will look like this time next year. But between the speed of AI and the speed of most enterprises in the real world, there is still a gap of many months, if not years. As long as we stay grounded in the actual conditions and needs of those businesses, there will always be time for us to adjust, and perhaps even discover more opportunities along the way.

What we most need to avoid in this process is end-state thinking: the belief that if AI can generate code, then it can do anything; the belief that if AI will eventually take over everything, then whatever we do now is meaningless. The real world in front of us does not look like that.

From a Vast Ocean, We Only Need One Drop

If the needs of enterprises around the world are a vast ocean, then we do not need a bucketful. We only need one drop. That is enough for a team our size to move at our own pace, stay focused on what we love, create value for the users inside that one drop, and find a sense of achievement there.

NocoBase has to stay focused on a precise kind of user. We are not trying to make every enterprise our target customer. Many people may not agree with the things we have listed here as long-term constants. That is fine. As long as the users in this one drop agree, that is enough.

So, Do Programmers and Software Still Have a Future?

I think the answer depends mostly on what we want, and on what we are willing to do.

If the ambition is to build another Salesforce, form a monopoly, and change the world, that is beyond our ability to judge. But for a product like NocoBase, built by a team of fourteen people, I believe there is absolutely a future. Not only are we not going to be killed, we may well have more opportunities ahead of us than before.

NocoBase used to live only inside the no-code crowd, and that crowd was very small. Today, NocoBase has also started attracting attention from AI users. More and more enterprises want to bring AI capability into real business operations. As long as we avoid end-state thinking, and do not assume that the leading model companies are capable of doing everything across every industry, every scenario, and every link in the chain, we will see how diverse enterprise demand really is. On the road to adopting AI, companies will need all kinds of infrastructure layers, along with the services that make them usable.

From that point of view, I believe some programmers, and some kinds of software, have a better future ahead of them than they did before.

Final Note

NocoBase 2.1 was released last week. Try connecting your AI agent to NocoBase and experience it for yourself.

GitHub: https://github.com/nocobase/nocobase

Announcing NocoBase 2.1.0

NocoBase — Mon, 15 Jun 2026 14:20:52 +0000

Originally published at https://www.nocobase.com/en/blog/2.1.0

NocoBase 2.1 is a major upgrade to AI capabilities, multi-app, and 2.0 adaptation. We've introduced the NocoBase CLI, making it easy for both people and AI Agents to connect to and manage NocoBase applications. From creating applications and AI-assisted building to enhanced AI Employees and an AI development plugin, it covers the full flow from environment onboarding to system building and business collaboration. We've also enhanced multi-app capabilities to make interaction and collaboration across apps easier. At the same time, we've added version control and continued to substantially round out 2.0 page support and core capabilities — more blocks, fields, actions, and plugins now support 2.0.

What's New

Introducing the NocoBase CLI

In this release, the NocoBase CLI (nb) is the core entry point for both regular users and AI Agents to connect to NocoBase.

The CLI is used to initialize, connect, and manage NocoBase applications in a local workspace. It covers several scenarios:

Install a new NocoBase application via Docker, npm, or Git, then save it as a CLI env
Connect to an existing NocoBase application and save it as a CLI env
Install, create, and activate plugins
Operate, back up, and manage NocoBase applications

Whether you want to plug AI into an existing system or spin up a new application from scratch, you can handle initialization and ongoing management through the CLI.

For teams, the CLI provides a standard entry point that AI Agents can understand and operate on — environment initialization, connection configuration, and runtime management all share the same flow.

The official release also adds a set of operations-related commands:

nb api: Call the NocoBase API through the CLI.
nb app: Manage application runtime state: start, stop, restart, logs, and upgrade.
nb backup: Create a backup and download it locally, or restore a local backup file to a target env.
nb config: Manage CLI default configuration.
nb db: Manage the built-in database of the selected env.
nb env: Manage NocoBase project environments, the current env, status, details, and runtime commands.
nb license: Manage commercial licenses and licensed plugins.
nb plugin: Manage plugins of the selected NocoBase env.
nb scaffold: Generate a NocoBase plugin development scaffold.
nb self: Check or update the NocoBase CLI itself.
nb source: Manage local source projects: download, develop, build, and test.

Related documentation:

AI-assisted building: replace manual configuration with conversation

AI-assisted building is one of the core experiences in this release. You can describe your business needs in natural language, and the AI helps complete data modeling, page configuration, permission setup, and workflow orchestration.

Compared with traditional low-code building, AI-assisted building has several clear advantages:

A lower barrier to entry — you don't need to be familiar with every configuration concept up front
A shorter path from requirement description to working prototype
Data, UI, and workflow configuration can be completed by the AI continuously

For example: "design a CRM data model for me", "create a customer management page for me", or "orchestrate a workflow that automatically deducts inventory after an order is created" — all of these can be handled by the AI within the scope of NocoBase's capabilities.

Related documentation:

AI-assisted building quick start

NocoBase Skills cover the full building flow

To help the AI truly understand NocoBase's configuration system, this release ships a set of domain knowledge packs that can be installed into AI Agents — NocoBase Skills.

Skills are standardized knowledge and operation wrappers organized around NocoBase's key capability domains, helping the AI more accurately understand object models, configuration structures, and execution boundaries.

We currently provide 8 Skills that cover the full building flow:

Environment management — environment checks, install/deploy, upgrade, and troubleshooting
Data modeling — create and manage tables, fields, and relations
UI building — create and edit pages, blocks, popups, and interaction reactions
Workflow management — create, edit, enable, and diagnose workflows
Permission configuration — manage roles, permission policies, user bindings, and risk assessment
Solutions — bulk-build entire business systems from YAML (still in beta, with limited stability)
Plugin management — view, enable, and disable plugins
Publish management — cross-environment publishing, backup/restore, and migration

With Skills, the AI can more accurately understand NocoBase's configuration system and provide smarter assistance when building and managing systems.

Note: NocoBase Skills are still being actively improved. NocoBase Skills are also installed automatically when you install and initialize the NocoBase CLI, so in most cases you don't need to install them separately.

Related documentation:

NocoBase Skills

AI development plugin

This release fills in the foundational capabilities needed for AI plugin development, so the AI can take part not only in application building but also in custom plugin development.

This shows up in three main areas:

A unified rsbuild/rspack build pipeline, consolidating plugin development and the frontend build system
A client-v2 capability and /v/ routing system aimed at AI development, preparing for the next-generation client plugin development
AI plugin development Skills that help the AI better understand plugin structure, code organization, and implementation patterns

Preparation around client-v2 includes:

@nocobase/app exposes the client-v2 entry
The kernel ships a @nocobase/client-v2 package with base components, utilities, and type definitions
Each plugin gets a /src/client-v2 directory
A new /v/ route is added — still being actively improved, available for early adopters
The kernel is gradually migrating to V2
Plugins are gradually migrating to V2

A unified build pipeline lowers the cost of frontend plugin development and debugging. The gradual rollout of client-v2 also gives the AI a more stable target structure for generating and maintaining plugin code.

In practice: you can describe a plugin requirement in natural language, and the AI helps generate the frontend and backend code, data tables, APIs, permission configuration, and i18n content.

Note: AI plugin development is only for client-v2-style new plugins. We will follow up with migration documentation and Skills for moving from client-v1 plugins to client-v2, to help you bring existing plugins into the new system.

Related documentation:

AI Employees enhancements

AI-assisted building answers "how do I use AI to build a system"; AI Employees answer "how do I let AI work inside the system to solve concrete business problems".

AI Employees existed in earlier releases, but in this release the related capabilities have been enhanced and the AI kernel has been rounded out:

MCP support
New AI Employee Atlas, playing a team-leader role and dispatching other AI Employees to complete tasks based on user intent
AI Employee workflow node
LLM-based web search tool
New aggregation query tool and report generation tool for producing business analysis reports
New localization engineer Lina, a built-in AI Employee from the localization plugin used for system localization translation, supporting incremental, selected, and full translation scopes

These improvements take AI Employees' extensibility, orchestration, and execution capabilities inside business systems to the next level. AI Employees can understand the current business context, invoke skills to execute specific tasks, participate in automated workflows, and combine external information to deliver analysis and output.

The official release also adds support for AI Employees to load files from workflow attachment fields and to handle multiple conversations in parallel, further improving the usability of AI Employees in real business processes.

Related documentation:

Version control

Version control helps you better manage your application's version iterations and change history. You can create, view, and restore different versions of an application, making it easy to switch versions and recover from issues during development and operations. Note: This feature requires the Professional edition or above.

Related documentation:

Multi-app enhancements

In this release, we have made some important enhancements to multi-app deployments, mainly in three areas:

New app block and app switcher, which let you surface entry points to other sub-applications on a page, making it easy for users to switch between the main app and sub-apps.

New app single sign-on. When a user enters a sub-app from the main app, or switches between sub-apps, the system attempts to automatically sign them in to the target sub-app using the currently logged-in user. Users no longer need to re-enter their credentials in each sub-app.

Calling sub-app APIs. In multi-app scenarios, each sub-app has its own independent API, distinguished by path prefix, parameters, and so on, making it easy to call a sub-app's API.

These enhancements are very practical for users running multi-app deployments, making it easier to exchange data and operate across multiple applications and improving the overall collaboration efficiency of multi-app systems.

Related documentation:

Workflow enhancements

This release enhances the controllability and observability of workflows:

Added timeout control — workflows that run too long are automatically terminated (subflows also support timeout configuration)
Added created-by and updated-by fields
Added a log field to node jobs, making it easier to view node logs while debugging
The Webhook trigger (synchronous mode) returns a 408 response status on timeout

Related documentation:

Workflow

Handwritten signature field

Added a handwritten signature field that lets you draw and save a signature in a form, suitable for approvals, confirmation sheets, receipts, and similar scenarios.

Related documentation:

Handwritten signature field

JS Item action

Added the JS Item action, which lets you run custom logic in an action by writing JS, working together with event flows to meet more flexible interaction needs.

Related documentation:

JS Item action

2.0 adaptation and new features

Beyond AI, this release continues to migrate key feature modules to 2.0, while also rolling out new features for real-world business scenarios.

New features

2.0 adaptation

Multilingual documentation

Added Indonesian and Vietnamese documentation

14 Open Source AI Agent Tools with the Most GitHub Stars

NocoBase — Fri, 12 Jun 2026 17:36:21 +0000

Originally published at https://www.nocobase.com/en/blog/github-open-source-ai-agent-tools-16

Recently, we have published several recommendation articles about open source AI Agent projects, and they have received attention, saves, and feedback from many developers. Many readers also mentioned that they would like to see more roundups of AI Agent tools across different directions and use cases.

In Reddit’s AI Agent community, developers have raised similar questions: there are more and more AI Agent tools and frameworks, but the hard part is figuring out which projects are suitable for real use cases and which ones are mostly hype.

This time, we focus on GitHub’s official ai-agent topic. We selected projects from the most-starred results and organized them in the order they appear on the topic page. Since the projects under this topic cover a wide range of types, we excluded some projects that are only loosely related to AI Agent tools, are too vertical in use case, or are closer to resource collections or single-purpose content generation. In the end, we selected 14 open source projects that are more suitable for this article.

💬 Hey, you're reading the NocoBase blog. NocoBase is the most extensible AI-powered no-code/low-code development platform for building enterprise applications, internal tools, and all kinds of systems. It’s fully self-hosted, plugin-based, and developer-friendly. → Explore NocoBase on GitHub

AI Agent-related projects cover a broad range of areas, so ranking purely by Star count does not fully explain their practical value. Therefore, this article first lists the basic information for each project, including official website, GitHub repository, Star count, and more. Then, each project is introduced from two angles:

Positioning: What type of AI Agent tool it mainly is, whether it focuses more on personal productivity, development assistance, web automation, knowledge management, or enterprise business systems.
Use cases: What specific problems it is better suited to solve, and whether it is more suitable for individual developers, team collaboration, or implementation inside enterprises.

Below are the 14 open source AI Agent projects we selected. Before the detailed introduction, you can quickly scan their positioning through the table.

Rank	Tool	GitHub Stars	Positioning
14	NocoBase	22.7k	AI-powered no-code business systems
13	OpenCLI	24.1k	Website-to-CLI / browser automation
12	Agent-Reach	26.3k	AI Agent web access / information retrieval
11	Google Workspace CLI	27k	Productivity suite CLI / Agent Skills
10	AionUi	28.1k	Local AI coworking workspace / multi-Agent management
9	OpenClaude	28.6k	AI Coding Agent / CLI tool
8	CopilotKit	34.7k	Agent frontend framework / Generative UI
7	Nanobot	44.1k	Lightweight AI Agent
6	Siyuan	44.4k	Self-hosted knowledge management / personal knowledge base
5	CowAgent	45.2k	AI Assistant / Agent Harness
4	Cherry Studio	47.2k	AI Productivity Studio
3	career-ops	52.7k	AI job search automation system
2	learn-claude-code	66.1k	Claude Code-like Agent Harness
1	Hermes Agent	191k	General AI Agent / Agent Harness

14. NocoBase

Official website: https://www.nocobase.com

GitHub: https://github.com/nocobase/nocobase

GitHub Stars: 22.7k

Project introduction

NocoBase is an open source AI-powered no-code / low-code platform for quickly building enterprise internal business systems, admin panels, and business applications that need continuous iteration.

As AI Agents gradually enter both development and business scenarios, enterprises need more than single-task automation. They need a system environment that can support data, permissions, pages, workflows, and activity logs. This is exactly the foundation NocoBase provides.

In NocoBase, AI can participate in application building. Users can describe business requirements in natural language, and AI can help create data models, configure pages, orchestrate workflows, and even assist with plugin development. After the system is generated, teams can continue checking and adjusting fields, relationships, pages, permissions, and workflows through the no-code interface.

NocoBase also supports configuring AI Employees inside business systems. AI Employees can work with page data, business context, tools, and knowledge bases to handle data analysis, content summaries, report generation, translation, unstructured content extraction, form filling, workflow node processing, and more. In this way, AI does not only help build the system. It can also continue participating in system operations.

Suitable scenarios

NocoBase is suitable for building enterprise internal systems that require data models, permission control, workflow orchestration, and long-term maintenance, especially in the following scenarios:

Enterprise internal business systems: CRM customer management, approval systems, ticketing systems, project management systems, operations backends, admin backends, and more.

Lightweight ERP and business management modules: procurement management, inventory management, order management, equipment management, asset management, archive management, customer follow-up, and more.
Extension and enhancement of existing systems: For enterprises that already have databases, ERP, CRM, or other business systems, NocoBase can help integrate data, configure pages, manage permissions, and orchestrate workflows.
A foundation for AI Agents to enter business workflows: NocoBase provides AI Agents with a clear business system environment, where business data has models, user operations have permissions, workflow transitions have rules, and later maintenance can continue through no-code configuration and plugin extensions.

🔎Related resources:

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

Official solution library: https://www.nocobase.com/en/solutions

13. OpenCLI

Official website: https://opencli.info

GitHub: https://github.com/jackwener/OpenCLI

GitHub Stars: 24.1k

Project introduction

OpenCLI converts websites, browser sessions, Electron apps, and local tools into CLI interfaces. Operations that originally required graphical interfaces can be wrapped as commands, allowing humans or AI Agents to call web capabilities, reuse logged-in browser sessions, and perform automated actions such as navigation, clicking, form filling, and data extraction.

Suitable scenarios

OpenCLI is suitable for scenarios where tasks need to be completed through webpages but no standard API is available:

Web automation: Read backend pages, query information, fill out forms, and extract platform data.
Agent tool interface: Wrap browser sessions and web capabilities as commands that AI Agents can call.

12. Agent-Reach

GitHub: https://github.com/Panniantong/Agent-Reach

GitHub Stars: 26.3k

Project introduction

Agent-Reach focuses on external information access for AI Agents. Through a CLI tool, it allows Agents to read and search content from platforms such as Twitter, Reddit, YouTube, GitHub, Bilibili, and Xiaohongshu, solving the access problem in information retrieval, content reading, and cross-platform research.

Suitable scenarios

Agent-Reach can be used for technology trend tracking, competitor research, social media sentiment analysis, content topic research, GitHub project organization, and cross-platform material collection. It is not a complete Agent platform by itself. Instead, it adds external information access capabilities to Agents, giving later analysis, summarization, and organization a richer information base.

11. Google Workspace CLI

GitHub: https://github.com/googleworkspace/cli

GitHub Stars: 27k

Project introduction

Google Workspace CLI is a command-line tool for Google Workspace. It covers Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Through command-line operations and structured JSON output, it turns capabilities scattered across different productivity apps into interfaces that are easier to call.

Suitable scenarios

For teams that heavily use Google Workspace, this type of tool makes it easier for AI Agents to enter daily office workflows, such as reading emails, managing calendars, organizing Drive files, operating Sheets, generating Docs, or processing Chat messages. Since it involves workplace data and account authorization, actual use should pay special attention to OAuth scopes, access boundaries, and data security.

🔎Related resources:

Agent Skills: https://github.com/googleworkspace/cli/blob/main/docs/skills.md

10. AionUi

Official website: https://www.aionui.com

GitHub: https://github.com/iOfficeAI/AionUi

GitHub Stars: 28.1k

Project introduction

AionUi is a local open source AI coworking app for AI CLI tools such as OpenClaw, Hermes Agent, Claude Code, Codex, OpenCode, and Gemini CLI. It provides built-in Agents, multi-Agent management, remote access, cross-platform use, and automation tasks, making it more like a desktop workbench for managing AI Agents and local work in one place.

Suitable scenarios

AionUi is suitable for people who use multiple AI Coding or Agent tools at the same time:

Multi-Agent management: Manage tools such as Claude Code, Codex, Hermes Agent, OpenCode, and Gemini CLI in one place.
Local workbench: Handle local files, coding tasks, web operations, and remote access in one workspace, reducing the need to switch between multiple tools.

9. OpenClaude

Official website: https://openclaude.gitlawb.com

GitHub: https://github.com/Gitlawb/openclaude

GitHub Stars: 28.6k

Project introduction

OpenClaude is an open source AI Coding Agent CLI that supports both cloud and local model providers, including OpenAI-compatible APIs, Gemini, GitHub Models, Codex, Ollama, Atomic Chat, and more. It brings prompts, tools, agents, MCP, slash commands, and streaming output into a terminal-first workflow.

Suitable scenarios

OpenClaude is mainly used in terminal development environments, such as code explanation, file modification, test generation, refactoring suggestions, and tool calling. It is flexible, composable, and supports many model choices, but it also requires users to have some development experience and manage model configuration, execution permissions, and code change review themselves.

8. CopilotKit

Official website: https://docs.copilotkit.ai

GitHub: https://github.com/CopilotKit/CopilotKit

GitHub Stars: 34.7k

Project introduction

CopilotKit is a frontend framework for Agents and Generative UI, supporting React, Angular, mobile, Slack, and other interfaces and platforms. It helps developers build AI Copilots, Agent interactions, shared state, and human-AI collaboration workflows inside their own products, rather than providing a standalone application for end users.

Suitable scenarios

When a product needs to embed an AI Copilot into its interface, CopilotKit provides a relatively complete frontend foundation. For example, it can let AI understand the current page state, assist with form filling, trigger in-app actions, generate UI content, or participate in a business workflow. It is more of a development framework, suitable for teams building AI products, SaaS applications, or internal systems.

🔎Related resources:

Build with Agents: https://docs.showcase.copilotkit.ai/build-with-agents

7. Nanobot

Official website: https://nanobot.wiki

GitHub: https://github.com/HKUDS/nanobot

GitHub Stars: 44.1k

Project introduction

Nanobot is a lightweight open source personal AI Agent that emphasizes real user ownership. It keeps the Agent core relatively simple while providing WebUI, chat channels, tools, memory, MCP, model routing, automation, deployment, and other capabilities.

Suitable scenarios

It is suitable for individual developers, small teams, or users who want to build lightweight AI Agents:

Personal AI Agent: Connect to Telegram, Discord, Slack, Email, and other entry points to handle daily tasks and automation workflows.
Agent prototype development: Quickly build a runnable Agent with tools, memory, MCP, model routing, and WebUI.

6. SiYuan

Official website: https://b3log.org/siyuan

GitHub: https://github.com/siyuan-note/siyuan

GitHub Stars: 44.4k

Project introduction

SiYuan is a privacy-first, self-hosted, fully open source personal knowledge management tool written in TypeScript and Go. It supports block references, backlinks, Markdown WYSIWYG editing, embedded SQL queries, web clipping, PDF annotation, databases, flashcards, AI writing, Q&A, and more.

Suitable scenarios

In the AI Agent context, SiYuan can be understood as a layer of knowledge infrastructure rather than a typical Agent framework. It is mainly used for personal knowledge management, research material organization, team knowledge accumulation, and local-first knowledge base building. When users want AI to better read, organize, and reuse long-term knowledge, this type of structured knowledge environment becomes especially important.

5. CowAgent

Official website: https://cowagent.ai

GitHub: https://github.com/zhayujie/CowAgent

GitHub Stars: 45.2k

Project introduction

CowAgent is an open source AI Assistant and Agent Harness. It supports task planning, tool and Skills calling, memory and knowledge, self-evolution, multi-model access, and multi-channel access. It also builds on the foundation of chatgpt-on-wechat in IM access and personal assistant scenarios.

Suitable scenarios

CowAgent focuses on connecting AI Assistants to multiple entry points and tool environments, such as webpages, servers, personal computers, the WeChat ecosystem, and other IM platforms. It is not just a chatbot. Instead, it aims to become a long-running personal assistant or automation assistant through task planning, tool calling, memory, and Skills extensions.

4. Cherry Studio

Official website: https://cherryai.com

GitHub: https://github.com/CherryHQ/cherry-studio

GitHub Stars: 47.2k

Project introduction

Cherry Studio is an AI Productivity Studio that supports intelligent chat, Autonomous Agents, 300+ assistants, and unified access to multiple frontier large language models. It is closer to a complete AI workbench for centrally managing models, assistants, knowledge bases, and daily AI workflows.

Suitable scenarios

Cherry Studio is designed for high-frequency AI use in daily work:

Multi-model workbench: Manage different large language models, assistants, knowledge bases, and daily AI workflows in one place.
AI productivity tool: Use it for writing, material organization, knowledge base Q&A, Agent usage, and team collaboration.

3. career-ops

Official website: https://career-ops.org

GitHub: https://github.com/santifer/career-ops

GitHub Stars: 52.7k

Project introduction

career-ops is an AI job search automation system based on Claude Code. It can turn an AI Coding CLI into a job search management center for job evaluation, resume generation, job portal scanning, batch processing, interview preparation, and opportunity tracking.

Suitable scenarios

career-ops is highly vertical and mainly focuses on personal job search workflows. Its value is not only in providing a “job search tool,” but also in showing how AI Agents can enter a clearly defined workflow and break job filtering, material generation, opportunity tracking, interview preparation, and batch processing into executable task chains.

2. learn-claude-code

Official website: https://learn.shareai.run

GitHub: https://github.com/shareAI-lab/learn-claude-code

GitHub Stars: 66.1k

Project introduction

learn-claude-code is an open source project for learning Claude Code-like Agent Harnesses. Built around the idea that “Agent product = Model + Harness,” it explains tools, knowledge, observation, action interfaces, permission boundaries, context management, multi-Agent collaboration, and more.

Suitable scenarios

learn-claude-code is more like systematic learning material for developers, helping users understand the mechanisms behind AI Coding Agents. It covers agent loop, tool use, permissions, hooks, memory, task systems, MCP, and multi-agent collaboration. It is suitable for individual learning and can also serve as internal training material for teams building Agent engineering capabilities.

1. Hermes Agent

Official website: https://hermes-agent.nousresearch.com

GitHub: https://github.com/NousResearch/hermes-agent

GitHub Stars: 191k

Project introduction

Hermes Agent is a self-improving AI Agent built by Nous Research. It is officially described as “The agent that grows with you.” It emphasizes that Agents can create and improve skills during continuous use, record and search past conversations, and gradually understand users’ long-term preferences and context.

Suitable scenarios

Hermes Agent is suitable for Agent scenarios that require long-term operation, long-term memory, and Skills accumulation:

Self-hosted Agent: Build a personal or team Agent that can run continuously, record historical conversations, and reuse skills.
Long-term collaboration assistant: Through memory, skills, and tool calling, the Agent can gradually accumulate context and working methods across repeated use.

🔎Related resources:

Skills System: https://hermes-agent.nousresearch.com/docs/user-guide/features/skills Skills Catalog: https://github.com/NousResearch/hermes-agent/blob/main/website/docs/reference/skills-catalog.md

FAQ

Q1: How should I choose between these tools?

A: You can first identify what type of problem you want to solve. If you want to improve personal productivity, you can prioritize Cherry Studio, Nanobot, Hermes Agent, and SiYuan. If you are developing AI Agents or AI Copilots, you can look at OpenClaude, CopilotKit, and learn-claude-code. If you want Agents to call external tools and web capabilities, you can look at OpenCLI, Agent-Reach, and Google Workspace CLI. If you are building enterprise business systems and implementing workflows, NocoBase is worth focusing on.

Goal	Recommended tools
Build enterprise internal systems	NocoBase
Web automation and tool calling	OpenCLI, Agent-Reach
Office system automation	Google Workspace CLI
AI Coding / terminal Agent	OpenClaude, learn-claude-code
In-product AI Copilot	CopilotKit
Personal AI assistant	Nanobot, Hermes Agent, CowAgent
Multi-model workbench	Cherry Studio
Knowledge management	SiYuan
Vertical Agent application reference	career-ops

Q2: Can non-technical teams use these AI Agent tools?

Yes, but it depends on the type of tool.

Projects such as OpenCLI, Agent-Reach, Google Workspace CLI, OpenClaude, CopilotKit, and learn-claude-code are more like CLI tools, development frameworks, or Agent engineering learning materials. They require some technical foundation.

Tools such as Cherry Studio and SiYuan have friendlier interfaces and are easier for business users to get started with directly.

NocoBase sits between the two. Non-technical users can use systems and AI Employees that have already been built. Users with some technical background can better configure data models, pages, permissions, and workflows. With development resources, teams can also extend it more deeply through plugins, APIs, Skills, and MCP.

Q3: What should enterprises pay the most attention to when using AI Agents?

When enterprises use AI Agents, they should not focus only on model capabilities. They also need to consider data, permissions, workflows, and auditing. Once an Agent enters a business system, it may access customer data, order information, approval workflows, contract content, or internal documents. Clear boundaries are required.

Key issue	Capabilities to focus on
Is data controllable?	Self-hosting, database permissions, data access scope
Are operations traceable?	Audit logs, activity logs, workflow records
Are permissions clear?	Role permissions, field permissions, data scope control
Do key actions require confirmation?	Human confirmation nodes, approval workflows, trigger conditions
Is Agent output stable?	Structured output, retry mechanisms, human review

The value of business system platforms such as NocoBase is that they place AI inside a system environment with permissions, workflows, and data models, rather than letting Agents directly face scattered data and uncontrolled operations. For scenarios such as approvals, customer service, data entry, and report generation, human confirmation and audit records remain very important.

Q4: Can multiple tools be combined?

Yes. The AI Agent ecosystem cannot be covered by a single tool. Many teams use different tools at different layers: some are responsible for building systems, some for calling webpages, some for writing code, some for knowledge management, and some for frontend AI interaction.

Combination scenario	Reference combination
Business system + AI Employee	NocoBase + AI Employee
Business system + external Coding Agent	NocoBase + Claude Code / Codex / OpenCode
Web operation + information organization	OpenCLI + Agent-Reach
In-product AI Copilot	CopilotKit + business system API
Knowledge base + Agent	SiYuan + Nanobot / Hermes Agent
Multi-model daily workbench	Cherry Studio + various model services

Conclusion

AI Agent tools are rapidly branching into different directions. Some tools focus on model calling and task execution, some focus on web automation and external information access, some focus on AI Coding and Agent Harnesses, and some are beginning to enter enterprise business systems and long-term process management.

For individual users, it is better to start with lightweight scenarios such as knowledge management, personal assistants, AI Coding, or browser automation. For enterprise teams, the more important question is whether an Agent can enter real business workflows and run stably under the constraints of data, permissions, workflows, and audit mechanisms.

If this article is helpful to you, feel free to share it with friends who are following open source AI Agent tools, AI automation, and enterprise internal system building.

Related reading:

Top 8 Open Source AI Assistant Tools by GitHub Stars

NocoBase — Wed, 10 Jun 2026 15:58:18 +0000

Originally published at https://www.nocobase.com/en/blog/top-open-source-ai-assistant-tools-github-stars

Over the past few weeks, we have organized several open source tools that work well with popular AI Agents:

💡After using Claude Code, you need these 6 open source tools

💡Do not let Codex generate apps from scratch: 6 composable open source projects

Recently, while browsing Reddit, we noticed that besides AI Agents, AI Assistants are still a topic many users actively discuss. Compared with Agents, which emphasize autonomous planning and task execution, Assistants are more like everyday work entry points. They can serve individuals, small teams, and enterprises.

In a discussion on r/AI_Agents, one user was looking for a personal AI Assistant that is actually worth using long term. They hoped it could help manage daily information such as notes, tasks, calendars, emails, reminders, and contacts.

Another discussion was more focused on enterprise and team scenarios. The user runs a service agency and needs to handle website content, emails, and social media work for small business clients, so they wanted to know which AI Assistants or AI tools would fit their needs.

From these discussions, we can see that AI Assistant needs roughly fall into two categories: personal use and enterprise or team use.

Personal AI Assistants: mainly help individual users manage daily information and improve productivity, such as organizing notes, following up on tasks, managing calendars, processing emails, setting reminders, calling local tools, or providing support in desktop and development environments.

Enterprise AI Assistants: better suited for teams and enterprises. They can connect to business systems, be embedded into application interfaces, handle customer communication, support content operations, automate workflows, and provide support around data, permissions, and task collaboration.

Based on this idea, we collected high-star projects ranked near the top under GitHub’s ai-assistant topic and selected 8 open source projects that are worth introducing in more detail.

Below, we will review them in two categories: enterprise AI Assistants and personal AI Assistants. Since personal AI Assistants usually have more direct use cases around desktops, development tools, and daily productivity, while enterprise AI Assistants often involve business systems, permission workflows, data management, application embedding, and team collaboration, this article will focus more on enterprise AI Assistants.

Category	Project	GitHub Stars	Positioning
Enterprise AI Assistant	NocoBase	22.7k	AI-powered no-code platform for building and maintaining business systems
Enterprise AI Assistant	NanoClaw	29.8k	AI Assistant with chat-based entry points and containerized runtime
Enterprise AI Assistant	CopilotKit	34.3k	Frontend framework for in-app AI Copilots and generative UI
Enterprise AI Assistant	Ruflo	58.6k	Multi-Agent collaboration and automation workflow assistant
Personal AI Assistant	DeepChat	6k	Desktop assistant that connects models, tools, and personal context
Personal AI Assistant	Everywhere	6k	Desktop context-aware AI Assistant
Personal AI Assistant	CopilotForXcode	6.1k	AI coding assistant for Xcode
Personal AI Assistant	Leon	17.3k	Open source personal AI Assistant

Enterprise AI Assistant

NocoBase

Website: https://www.nocobase.com/

Online Demo: https://demo.nocobase.com/new

Documentation: https://docs.nocobase.com/

GitHub: https://github.com/nocobase/nocobase

Stars: 22.7k

Introduction

NocoBase is an open source AI-powered no-code platform for quickly building enterprise internal business systems. In NocoBase, users can describe business requirements in natural language and let AI help with data model design, page configuration, workflow orchestration, permission setup, plugin management, and more. NocoBase also supports AI Employees, AI Skills, CLI, and other capabilities, allowing AI to continue working around existing business systems instead of stopping at one-off app generation.

This is especially important for enterprise internal systems. Many business applications are not finished after being generated once. They often need continuous adjustments to fields, permissions, workflows, pages, and data relationships. The value of NocoBase is that it provides AI with a structured system environment, allowing AI to work within existing data models, permissions, workflows, and plugin systems.

Core features

AI participates in business system building

NocoBase supports describing business requirements in natural language and letting AI help with the initial creation of data tables, fields, relationships, pages, and workflows. For example, users can describe a customer management, ticket management, contract approval, or project dashboard scenario. AI can first generate the system foundation, and the team can then review and adjust it.

This approach is better suited for enterprise internal systems, because business systems usually require clear data structures, role permissions, and workflow rules. AI improves building efficiency, while humans confirm business logic and control system boundaries.

🔎Related resources:

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

AI Employees can continue participating in system operations

NocoBase’s AI Employees can automatically use page data and structure as context, understand business scenarios, and directly execute tasks. They can summarize emails, analyze data, organize unstructured content and automatically fill forms, design data models, and even write JavaScript code. Each AI Employee has independent Skills, tools, and knowledge bases. Enterprises can create any number of AI Employees to build their own AI team.

No-code capabilities reduce later maintenance costs

Many AI generation tools can quickly generate code, but later maintenance often depends on developers. NocoBase is different. After AI generates the system, users can still enter the no-code interface to continue modifying fields, pages, menus, action buttons, permissions, and workflows.

For business teams, this means the system does not remain a one-off demo. Whenever the business changes, teams can continue adjusting it inside the platform, without needing to return to the code development process every time.

Suitable for enterprise-level data, permissions, and workflows

When enterprise AI Assistants are actually implemented, data, permissions, and workflows are unavoidable. NocoBase has capabilities such as data models, role permissions, workflows, plugin extensions, and multiple data sources, making it a strong foundation for AI Assistants to work inside business systems.

For example, AI can work around business objects such as customers, orders, tickets, projects, inventory, and contracts. At the same time, different roles can have different data access scopes and operation permissions, preventing everyone from seeing the same information or performing the same actions.

Suitable for starting from specific scenarios

When using NocoBase, it is not recommended to ask AI to build a complete ERP or complex enterprise system from the beginning. A better approach is to start with a clear small scenario, such as customer management, purchase requests, equipment ledgers, after-sales tickets, contract approval, project dashboards, or inventory records.

After one specific scenario works well, you can gradually expand fields, pages, workflows, and permissions. This makes it easier for AI-generated results to match the business and makes later review and maintenance easier for the team.

Suitable scenarios

CRM customer management system
Approval systems
Ticketing systems
Project management systems
Lightweight ERP modules such as procurement, inventory, and orders
Operations backends and admin backends
Equipment management, asset management, and archive management
Customer follow-up and service management
Enterprise internal systems that require private deployment
Business applications that require permissions, workflows, data models, and continuous adjustment
Teams that want to combine AI and no-code capabilities to build internal systems

NanoClaw

GitHub: https://github.com/nanocoai/nanoclaw

Official website: https://nanoclaw.dev

Stars: 29.8k

Introduction

NanoClaw is a lightweight AI Assistant project focused on running Agents in containers and connecting to messaging channels such as WhatsApp, Telegram, Slack, Discord, and Gmail. It is more like an enterprise-focused AI Assistant with chat-based entry points and container isolation, making it suitable for users who want to call Agents, handle tasks, and arrange automation workflows through chat tools.

Compared with ordinary chat assistants, NanoClaw places more emphasis on security isolation and controllable runtime environments. Each Agent can run in an independent container, reducing its impact on the host system and other tasks.

Core features

Containerized runtime: Agents run in independent containers, making it easier to isolate the file system and runtime environment.
Rich messaging channels: Supports Telegram, Discord, WhatsApp, Slack, Gmail, and other entry points, making it suitable for connecting AI Assistants to daily collaboration tools.
Lightweight and customizable: Compared with large Agent systems, NanoClaw emphasizes clear code structure, easy understanding, and convenient customization.

Suitable scenarios

Calling AI Assistants through messaging tools such as Telegram, Discord, and Slack.
Building a self-hosted task processing entry point for individuals or teams.
Running Agent tasks in a safer and isolated environment.

CopilotKit

GitHub: https://github.com/CopilotKit/CopilotKit

Official website: https://docs.copilotkit.ai

Stars: 34.4k

Introduction

CopilotKit is a frontend framework for building AI Copilots, generative UI, and Agent applications. It is better understood as a development framework for in-app AI Assistants. It can embed Agent capabilities into interfaces users already use, such as Web, mobile apps, Slack, and Teams.

Its focus is not only providing a chat window. It also supports generative UI, shared state, and human confirmation workflows, making it suitable for teams that need to deeply integrate AI Assistants into product interactions.

Core features

In-app Copilot: Embed AI Assistants directly into existing applications, instead of asking users to switch to a separate chat tool.
Generative UI: Agents can generate or update UI components based on task status and user intent.
Human confirmation workflows: Supports human-in-the-loop, allowing users to confirm, modify, or take over tasks at key steps.

Suitable scenarios

Embedding an AI Copilot into SaaS products.
Building AI Assistants that can read application state, call tools, and generate interfaces.
Teams that need to integrate Agent workflows into Slack, Teams, or Web applications.

Ruflo

GitHub: https://github.com/ruvnet/ruflo

Official website: https://flo.ruv.io

Stars: 58.6k

Introduction

Ruflo is a multi-Agent collaboration platform for Claude Code and Codex, used to coordinate multiple specialized Agents, automated workflows, and team-level tasks. It is more like the Agent collaboration foundation behind enterprise AI Assistants, and is suitable for complex development, testing, security, documentation, architecture, and DevOps scenarios.

Its core value is expanding the capability of a single Agent into multi-Agent collaboration, allowing tasks to be split, routed, executed, and remembered.

Core features

Multi-Agent collaboration: Supports multiple specialized Agents working together on development, testing, security, documentation, and other tasks.
Designed for complex workflows: Can work with Claude Code / Codex to handle coding, testing, auditing, documentation generation, and other workflows.
Plugin and memory capabilities: Provides a plugin system, vector memory, and task coordination capabilities, making it suitable for more complex Agent working environments.

Suitable scenarios

Multiple Agents need to collaborate on development tasks.
Teams want to automate code review, test generation, documentation maintenance, security scanning, and similar workflows.
Teams need to extend more complex Agent collaboration capabilities on top of Claude Code or Codex.

Personal AI Assistant

DeepChat

GitHub: https://github.com/ThinkInAIXYZ/deepchat

Official website: https://deepchat.thinkinai.xyz

Stars: 6k

Introduction

DeepChat is an open source desktop AI Assistant platform that supports multiple cloud and local large language models, and integrates MCP tool calling, Skills, ACP Agent integration, and remote control capabilities. It is more like a desktop assistant that connects models, tools, and personal context.

For individual users, DeepChat’s advantage is that it brings multi-model chat, local models, tool calling, search enhancement, and skill workflows into one desktop application.

Core features

Unified multi-model management: Supports multiple model providers, including OpenAI, Gemini, Anthropic, DeepSeek, and Ollama.
Tool and skill support: Built-in MCP, Skills, and ACP Agent integrations can extend task capabilities for code review, document processing, PDFs, PPTs, spreadsheets, and more.
Remote control: Supports controlling DeepChat sessions through Telegram, Feishu, QQBot, Discord, WeChat iLink, and other channels.

Everywhere

GitHub: https://github.com/Sylinko/Everywhere

Official website: https://everywhere.sylinko.com

Stars: 6k

Introduction

Everywhere is a desktop AI Assistant focused on screen context awareness and contextual understanding. It can perceive the current application and screen content, allowing users to call AI for help in the current work environment without frequently taking screenshots, copying content, or switching windows.

It is more like a desktop context-aware assistant, suitable for individual users when reading, translating, troubleshooting, summarizing, and working across applications.

Core features

Screen context awareness: Understands the current screen and application environment, reducing copy-paste and window switching.
Quick invocation: Uses shortcuts to call the AI Assistant in the current scenario, making it closer to desktop workflows.
Supports multiple models and MCP tools: Can combine different LLMs and MCP tools to complete more operations in the desktop environment.

GitHub Copilot for Xcode

GitHub: https://github.com/github/CopilotForXcode

Official website: https://github.com/github/CopilotForXcode

Stars: 6.1k

Introduction

GitHub Copilot for Xcode is an AI coding assistant for Xcode, mainly serving Swift, Objective-C, iOS, and macOS development scenarios. It is more like a developer assistant embedded directly into Xcode, providing code completion, chat, code review, Agent Mode, and other capabilities.

For developers in the Apple ecosystem, its value is bringing AI programming assistance into the native development environment and reducing the need to switch back and forth between Xcode and other AI tools.

Core features

Native Xcode integration: Built for Swift, Objective-C, iOS, and macOS development, and used directly in Xcode.
Code completion and chat: Supports code suggestions, Copilot Chat, code review, and other features.
Agent Mode: Can understand and modify codebases, search related files, create files, and run MCP tools.

Leon

GitHub: https://github.com/leon-ai/leon

Official website: https://getleon.ai

Stars: 17.3k

Introduction

Leon is an open source personal AI Assistant built around tools, context, memory, and Agent-style execution. It is more like a personal assistant that can run locally or on a server, suitable for users who value privacy, control, and extensibility.

Compared with ordinary chat assistants, Leon emphasizes completing tasks through real tools and combining memory with context, making its answers and actions closer to the user’s real environment.

Core features

Clear personal assistant positioning: Designed for personal tasks, voice, automation, memory, and local environments.
Supports tools, skills, and memory: Can use local tools, skills, and hierarchical memory to complete more specific tasks.
Balances local and remote models: Supports local and remote AI providers, making it easier to choose between privacy and capability.

FAQ

1. What should you consider when choosing an open source AI Assistant?

When choosing an open source AI Assistant, you can focus on five aspects: whether the project is actively maintained, whether it supports your use case, whether it can connect to existing tools or systems, whether it supports self-hosting or private deployment, and whether it has clear documentation and an active community.

Individual users can prioritize ease of use, model support, local tool calling, and desktop experience. Enterprise users should focus more on permissions, data structures, workflow automation, system integration, and long-term maintenance capabilities.

2. If I want to build internal business systems for an enterprise, which AI Assistant project should I choose?

If your goal is to build enterprise internal business systems such as CRM, approval systems, ticketing systems, project management, inventory management, and operations backends, you can look at NocoBase first.

NocoBase is better suited for supporting enterprise business data, permissions, workflows, and page configuration. It can not only help build systems with AI, but also continue adjusting fields, pages, permissions, and workflows through a no-code interface after generation. For enterprise internal systems that require long-term maintenance, this type of structured platform is more reliable.

3. If I only need a desktop AI Assistant for personal use, which one should I choose?

If you mainly use it personally and want to use multiple models, process files, call tools, and organize information from one desktop app, you can first look at DeepChat or Everywhere.

DeepChat is better suited for bringing multiple models, MCP, Skills, and remote control capabilities into one desktop application. Everywhere emphasizes screen context awareness and contextual understanding, making it suitable for reading, translating, troubleshooting, and summarizing webpages or documents.

4. If I am a developer and want to use an AI Assistant inside development tools, which one should I choose?

If you are a developer in the Apple ecosystem and mainly use Xcode to build iOS, macOS, Swift, or Objective-C projects, you can look at GitHub Copilot for Xcode.

It is better suited as a developer assistant embedded directly into Xcode, providing code completion, chat, code review, Agent Mode, and other capabilities. If your needs lean more toward multi-Agent collaboration, code review, test generation, documentation maintenance, and DevOps workflows, you can also look at Ruflo.

5. If I want to embed an AI Assistant into my own product interface, which one should I choose?

If you are building a SaaS product, Web application, or internal product and want to embed an AI Assistant directly into the application interface, you can first look at CopilotKit.

CopilotKit is better suited for building in-app Copilots. It allows AI Assistants to read application state, call tools, generate interfaces, and add human confirmation workflows at key steps. For teams that want to add AI Copilots, generative UI, or Agent workflows to products, it is a better fit.

6. How should I choose if I want to build an open source personal AI Assistant?

Leon leans more toward the personal assistant direction and is suitable for personal tasks, voice interaction, tool calling, memory, and automation scenarios. It is suitable for users who value privacy, self-hosting, long-term memory, and extensibility. If you want an assistant that can gradually connect to your local environment and personal workflows, Leon is closer to that direction than a simple chat tool.

7. Is NocoBase only for enterprises? Can individual users use it?

NocoBase is not only for enterprises. Individual users can also use it to build their own management systems or knowledge bases. Its open source edition is free and friendly to individual users.

For example, individuals can use NocoBase to build knowledge bases, reading logs, task management systems, resource libraries, project dashboards, customer follow-up tables, content topic libraries, and other systems. As long as your needs involve data tables, fields, relationships, pages, and long-term organization, NocoBase can serve as a lightweight personal management platform.

⭐ If this article inspired you, feel free to share it with friends who are also interested in open source AI tools and productivity improvement.

Related reading

6 Open Source Tools to Use with WorkBuddy

NocoBase — Fri, 05 Jun 2026 17:13:58 +0000

Originally published at https://www.nocobase.com/en/blog/workbuddy-open-source-tools

What is WorkBuddy?

WorkBuddy is an AI workspace for workplace tasks launched by Tencent. It is mainly designed for enterprise office work, file processing, data analysis, and multi-step task handling.

Compared with tools like OpenClaw, Claude Code, and Codex, WorkBuddy has a different focus. OpenClaw emphasizes open Agent capabilities and a cross-platform skill ecosystem. Claude Code and Codex are better suited for code generation, development collaboration, and engineering tasks. WorkBuddy is more focused on workplace scenarios. It can connect to common communication and collaboration tools such as WeChat, QQ, WeCom, Feishu, and DingTalk, allowing users to start tasks from familiar work entry points.

If a team wants to connect more deeply with enterprise business systems and internal workflows, WorkBuddy can also serve as the AI task entry point and orchestration layer. WorkBuddy receives instructions, breaks down tasks, and returns results. Open source tools provide the underlying business systems, automation workflows, CRM, project management, data APIs, and BI analytics capabilities.

This article introduces several open source tools that work well with WorkBuddy. We will look at what capabilities they can provide for enterprises and what typical scenarios they can cover when combined with WorkBuddy.

1. NocoBase: suitable for building custom business systems that WorkBuddy can call

Official website: https://www.nocobase.com/

GitHub: https://github.com/nocobase/nocobase

GitHub Stars: 22.3k

Documentation: https://docs.nocobase.com/

Related resources:

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

WorkBuddy + NocoBase: https://docs.nocobase.com/en/ai/workbuddy

Product introduction

NocoBase is an AI-powered open source no-code / low-code development platform for quickly building enterprise applications, internal tools, and various business systems. It supports private deployment and is built on a plugin-based architecture, making it suitable for enterprises to build CRM, ERP, approval systems, ticketing systems, inventory systems, project management systems, operations backends, and other systems based on their own business needs.

For teams that want to connect WorkBuddy to internal tools, NocoBase is better suited as the business application layer. It provides stable data structures, permission boundaries, process rules, and callable system capabilities.

NocoBase also designs its AI capabilities around real business systems. It supports AI Employees, AI Skills, CLI, MCP, and more. AI Employees can act as intelligent assistants inside the system and help with data queries, content generation, task handling, and other work. AI Skills help external Agents understand how NocoBase is configured and what they can and cannot operate on. The CLI lets Agents execute installation, creation, modification, and other operations through commands. MCP provides a more standard entry point for external AI tools to connect to NocoBase.

Core advantages

Data model driven: NocoBase supports defining data tables, fields, and relationships first, then building pages and interactions. This makes it more suitable for complex business systems than simple form collection.
Suitable for private deployment: Enterprises can deploy the system on their own servers, making it better suited for internal systems with requirements for data security, permission control, and long-term maintenance.
Complete permission and workflow capabilities: It supports role permissions, field permissions, data permissions, and operation permissions. Workflows can also handle approvals, notifications, data updates, Webhooks, HTTP requests, and other processes.
Flexible plugin architecture: NocoBase uses a plugin-based microkernel architecture. Features can be extended through plugins, making it suitable for enterprises that need to customize business logic beyond standard capabilities.
AI capabilities closer to business systems: NocoBase supports AI Employees, AI Skills, knowledge bases, and other capabilities. These can work around pages, data tables, selected records, and business rules.

Typical use cases with WorkBuddy

In many scenarios, WorkBuddy receives instructions, breaks down tasks, and returns results, while NocoBase provides specific business objects and system capabilities, such as customers, orders, approvals, tickets, inventory, and projects.

Here are 3 common scenarios:

CRM Enterprises can use NocoBase to build a customer management system and centrally maintain customer profiles, follow-up status, customer tiers, owners, contract amounts, and other information. Sales managers can send instructions directly from WeCom or Feishu and ask WorkBuddy to query recently added customers, leads that have not been followed up for a long time, and key customers. NocoBase provides customer data, permissions, and filtering logic. AI Employees or related Skills can further help organize follow-up priorities, generate customer summaries, or create sales to-do lists.

Ticket management In after-sales or operations teams, NocoBase can record ticket status, issue type, priority, handler, and deadline. During daily checks or weekly reviews, teams can ask WorkBuddy to summarize overdue tickets, high-priority issues, and pending items, then classify them by owner, urgency, or issue type, making it easier to confirm the handling order.

Project management For managers, approvals and project progress are often scattered across multiple nodes. NocoBase can manage approval workflows, project milestones, owners, risks, and progress status. WorkBuddy can extract pending approvals, delayed tasks, and project risks based on instructions, then generate summaries by department, owner, or priority.

2. Activepieces: suitable for connecting WorkBuddy to more automation workflows

Official website: https://www.activepieces.com/

GitHub: https://github.com/activepieces/activepieces

GitHub Stars: about 23k

Documentation: https://www.activepieces.com/docs

Product introduction

Activepieces is an open source AI automation platform for building automation workflows across tools and systems. It can connect APIs, Webhooks, databases, spreadsheets, email, CRM, project management tools, and other third-party services, turning operations scattered across different tools into reusable workflows.

Activepieces works well with WorkBuddy in scenarios where instructions start from an office entry point and actions happen across multiple systems. WorkBuddy can receive requests from WeCom, Feishu, DingTalk, and other work entry points. Activepieces then executes the underlying workflow, such as reading data, calling APIs, syncing records, sending notifications, or triggering follow-up tasks.

Core advantages

Strong cross-tool connectivity: Suitable for connecting APIs, Webhooks, databases, and third-party applications, reducing repetitive manual work.
Suitable for turning automation into reusable workflows: Processes such as lead syncing, notification pushing, spreadsheet updates, task assignment, and data organization can be turned into fixed workflows.
Supports self-hosting: Enterprises can deploy it in their own environment, making it easier to manage keys, data, and execution logs.
Close to how AI Agents call tools: Activepieces pieces can be used as MCP servers, making it easier to combine with Agent tools.

Typical use cases with WorkBuddy

Activepieces is suitable for cross-system automation. For example, website forms, customer support feedback, GitHub Issues, and sales leads may be scattered across different tools. Teams can first use Activepieces to configure workflows for data reading, deduplication, classification, and syncing. Then, with a simple WorkBuddy instruction such as “organize today’s new leads and group them by source and priority,” the result can be returned to a group chat, document, or spreadsheet.

3. Twenty: suitable for building a self-hosted CRM data layer

Official website: https://twenty.com/

GitHub: https://github.com/twentyhq/twenty

GitHub Stars: 49k

Documentation: https://twenty.com/developers

Product introduction

Twenty is an open source CRM, officially positioned as an open source alternative to Salesforce. It is suitable for managing companies, contacts, customer relationships, opportunities, tasks, notes, and sales processes. Technical teams can also customize it based on their own business processes.

If an enterprise wants to keep customer data under control and avoid relying completely on a closed CRM, Twenty can serve as the customer data layer behind WorkBuddy. Customer records, opportunities, and sales follow-up records are stored in Twenty, while WorkBuddy receives query, organization, and reminder requests from workplace entry points.

Core advantages

Focused on CRM scenarios: Better suited for customer management, opportunity follow-up, sales tasks, and customer data organization.
Open source and self-hostable: Enterprises can better control customer data, system environments, and future customization.
Suitable for technical teams to customize: Objects, fields, and business structures can be adjusted around the enterprise’s own sales process.
More focused business objects: Compared with general-purpose internal tools, Twenty’s data structure is closer to the daily work of sales teams.

Typical use cases with WorkBuddy

Sales teams can maintain customer profiles, company information, opportunity stages, follow-up records, and next actions in Twenty. When sales managers need to view key customers, they do not necessarily need to enter the CRM backend and filter records one by one. They can initiate queries through WorkBuddy, such as “find high-value customers who have not been followed up for 7 days,” “organize new opportunities this week,” or “list high-value deals with no next action.”

Twenty stores and manages sales data. WorkBuddy organizes query results into follow-up lists, reminder summaries, or weekly reports. This helps teams quickly identify customers and opportunities that need priority handling, and reduces the risk that sales data stays buried in the CRM backend without timely review.

4. Plane: suitable for letting WorkBuddy read project status and task progress

Official website: https://plane.so/

GitHub: https://github.com/makeplane/plane

GitHub Stars: 49.8k

Documentation: https://docs.plane.so/

Product introduction

Plane is an open source project management tool for tracking Issues, managing Cycles, maintaining Roadmaps, and storing project documents and team tasks. It is better suited for product, engineering, and project management teams to manage release plans, task status, project risks, and collaboration rhythm.

Plane also officially emphasizes collaboration between teams and agents. In the WorkBuddy scenario, Plane can serve as the project collaboration layer: projects, tasks, owners, status, priority, and release plans are stored in Plane, while WorkBuddy brings these statuses into the team’s daily work entry points.

Core advantages

Suitable for product and engineering collaboration: It can manage Issues, Cycles, Roadmaps, documents, and team tasks.
Clearer task status: Suitable for tracking priority, owner, release plans, and delay risks.
Supports self-hosting: More suitable for teams that need control over project data and engineering information.
Suitable for use with Agents: Plane already emphasizes the collaboration space for teams and agents, making it suitable for combinations around task progress, project status, and knowledge accumulation.

Typical use cases with WorkBuddy

Product managers can ask WorkBuddy in Feishu, “Which P0 issues in this release are still open?” Project owners can ask, “Which tasks are delayed this week, and who are they blocked on?” Engineering leads can also ask WorkBuddy to organize high-priority Issues by module.

In this scenario, Plane records projects, Issues, Roadmaps, and owner information. WorkBuddy initiates queries from the workplace entry point and organizes the results into summaries or reminders. For teams with many tasks, fast release cycles, and frequent status synchronization needs, this combination can reduce the cost of repeatedly opening the project backend to check status.

5. Directus: suitable for turning existing databases into callable data interfaces

Official website: https://directus.io/

GitHub: https://github.com/directus/directus

GitHub Stars: 34.2k

Documentation: https://directus.io/docs

Product introduction

Directus is an open source data platform that can generate a management interface, REST API, and GraphQL API on top of SQL databases. It is suitable for teams that already have databases but lack a user-friendly backend, standard interfaces, or a unified data access layer.

Many enterprises do not lack data. The problem is that data is scattered across legacy systems, database tables, or multiple internal applications. Letting an Agent access a database directly is relatively risky, and asking business users to write SQL is unrealistic. Directus can add an API and permission management layer between the database and WorkBuddy, making existing data easier to query, organize, and call.

Core advantages

Connects to existing SQL databases: Suitable for wrapping existing databases into easier-to-use data services.
Automatically generates APIs: Data can be accessed through REST, GraphQL, or SDKs.
Provides a data management interface: It is not only an API layer, but can also be used as a data backend.
Suitable for progressive modernization: Enterprises do not need to rebuild the whole system. They can first expose key data tables through Directus.

Typical use cases with WorkBuddy

For example, an enterprise may already have customer databases, order databases, inventory tables, or content asset libraries, but the data is scattered across legacy systems, making it difficult for business users to query quickly. The enterprise can first use Directus to connect key data tables, configure permissions and APIs, and then let WorkBuddy query the data through interfaces.

Employees can initiate requests from workplace entry points, such as “check today’s new orders,” “find products whose inventory is below the safety stock level,” or “summarize the last 3 transactions of a customer.” Directus provides APIs and permission boundaries. WorkBuddy turns natural language requests into query tasks and organizes the results into easier-to-read summaries.

6. Metabase: suitable for letting WorkBuddy read reports and business metrics

Official website: https://www.metabase.com/

GitHub: https://github.com/metabase/metabase

GitHub Stars: 47k

Documentation: https://www.metabase.com/docs

Product introduction

Metabase is an open source BI tool for building data dashboards, business reports, and self-service analytics. It can connect to databases, allowing teams to build metric systems and dashboards around sales, operations, product, finance, customer support, and other data.

If Directus is better suited for turning databases into APIs, Metabase is better suited for turning data into business questions and metric dashboards. When used with WorkBuddy, Metabase can serve as the data analytics layer, allowing managers to get key metrics and business summaries through workplace entry points.

Core advantages

Suitable for business data analysis: It can connect to databases and build dashboards, charts, and reports.
Lowers the barrier to data queries: Business users can view metrics through visual interfaces and do not necessarily need to write SQL.
Suitable for management and operations teams: Common scenarios include sales dashboards, channel analysis, user growth, ticket trends, and inventory analysis.
Provides API capabilities: Metabase provides APIs that can be used to automate some backend tasks and data query scenarios.

Typical use cases with WorkBuddy

Managers do not necessarily open BI systems every day to browse multiple dashboards, but they usually need to quickly understand key changes. For example, “How did this week’s sales revenue change compared with last week?” “Which channels did today’s new registered users come from?” “Which product line had the fastest increase in ticket volume?” “Which pages had the most obvious drop in conversion rate?” This makes the combination of Metabase and WorkBuddy well suited for business data summaries.

Metabase connects databases and stores metrics and dashboards. WorkBuddy brings these metrics into WeCom, Feishu, or DingTalk. Users can ask questions directly from workplace entry points, and WorkBuddy can call the relevant reports or data interfaces, then return structured summaries.

FAQ

1. Can WorkBuddy directly connect to traditional SaaS, ERP, or CRM?

Yes, but it depends on whether the system itself provides APIs, Webhooks, plugins, MCP, or other callable capabilities.

Many traditional SaaS, ERP, and CRM systems have relatively fixed data structures and process rules. The systems can be used, but their field relationships, interface capabilities, permission boundaries, and audit records may not be suitable for direct Agent access.

For simple queries, notifications, or data synchronization, traditional systems can also be connected through APIs or integration platforms. But if an enterprise wants to flexibly configure data, permissions, and workflows around objects such as customers, orders, approvals, tickets, inventory, and projects, open source tools or self-hostable platforms are usually better suited as the layer that hosts these capabilities.

2. Why choose open source tools to use with WorkBuddy?

Open source tools are usually better suited for teams that need self-hosting, data control, open interfaces, and long-term extensibility.

Enterprises can better understand where data is stored, how system permissions are configured, how interfaces are called, and how operation logs are kept. They can also carry out secondary development or system integration based on their own needs. For scenarios involving customer information, project data, order records, business metrics, and internal workflows, this level of control is especially important.

WorkBuddy handles the workplace entry point and task orchestration. Open source tools host capabilities such as business systems, automation workflows, CRM, project management, data APIs, and BI analytics. Together, they connect everyday workplace entry points with specific business systems.

3. If we want to build system-level internal tools, which one should we look at first?

NocoBase.

If an enterprise wants to build CRM, ERP, ticketing systems, approval systems, inventory management, project management, or operations backends, NocoBase is better suited as a system-level internal tool platform. It uses a data model driven architecture, making it suitable for defining business objects such as customers, orders, tickets, approvals, inventory, and projects first, and then configuring pages, permissions, workflows, and plugins.

At the same time, NocoBase has already published WorkBuddy integration documentation, making it directly relevant to this topic. For teams that need to manage complex business data, permission boundaries, and workflow rules, NocoBase offers broader coverage than a single CRM, a single automation tool, or a single BI tool.

4. If the main goal is dashboard monitoring and business data analysis, which one should we choose?

Metabase.

Metabase is better suited for connecting databases, building dashboards, maintaining business metrics, and generating data reports. Scenarios such as sales dashboards, channel analysis, user growth, ticket trends, inventory changes, and conversion rate changes are all suitable for Metabase.

When paired with WorkBuddy, managers can query key metrics from workplace entry points, such as “How did this week’s sales revenue change compared with last week?” “Which channels did today’s new users mainly come from?” and “Which product line had the fastest increase in ticket volume?” Metabase stores the metrics and dashboards, while WorkBuddy initiates queries and returns structured summaries.

5. What should an enterprise do if it already has databases but lacks a unified query entry point?

Many enterprises already have customer databases, order databases, inventory tables, or content asset libraries, but the data is scattered across legacy systems or internal databases. When business users want to query data, they often need to enter multiple backends or ask technical colleagues to export data temporarily.

Directus can generate a management interface, REST API, and GraphQL API on top of SQL databases, which is equivalent to adding a clearer data access entry point for existing databases. When paired with WorkBuddy, employees can query information such as “today’s new orders,” “products whose inventory is below the safety stock level,” and “the last 3 transactions of a customer” from workplace entry points.

6. Does using WorkBuddy with open source tools require technical teams?

It depends on how deeply it is used.

For simple queries, reminders, information organization, or report summaries, business teams can start with the capabilities of existing tools. But if WorkBuddy needs reliable integration with internal systems, such as calling APIs, configuring permissions, designing workflows, managing keys, and keeping operation logs, IT or development teams need to be involved.

A safer approach is to start with low-risk, high-frequency scenarios, such as customer follow-up lists, project progress summaries, overdue ticket reminders, business data dashboards, and inventory exception queries. After the workflow becomes stable, it can gradually expand to more complex system operations and cross-tool automation.

7. When is WorkBuddy a good choice?

WorkBuddy is a good fit if a team mainly collaborates through WeChat, QQ, WeCom, Feishu, DingTalk, and similar entry points, and wants to use AI Agents to handle daily office tasks such as file organization, spreadsheet analysis, PPT generation, meeting summaries, and task assignment.

If the enterprise also wants to further connect internal tools, CRM, project management, data dashboards, automation workflows, and other systems, it can use WorkBuddy as the task entry point, and pair it with open source tools such as NocoBase, Activepieces, and Twenty to add specific business systems and data capabilities.

If this article is helpful, feel free to share it with friends who are following AI Agents.

Related reading

Weekly Updates: Add Dynamic API Command Compatibility Guards

NocoBase — Thu, 04 Jun 2026 08:03:53 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260604

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated with three branches: main , next and develop.

main：The most stable version to date, recommended for installation;
next：Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It's mainly for test users to collect feedback and optimize functions further. Ideal for test users who want to experience new features early and give feedback;
develop：Alpha version, contains the latest feature code, may be incomplete or unstable, mainly for internal dev and rapid iteration. Suited for tech users interested in product's cutting-edge, but with potential issues and incomplete functions. Not for production use.

main

v2.0.61

Release date: 2026-06-03

🚀 Improvements

[client] Enhanced autocomplete support for some built-in RunJS functions. (#9481) by gchust
[undefined] Updated the Embed NocoBase documentation for the open-source plugin. (#9642) by zhangzhonghe Reference: Embed NocoBase

🐛 Bug Fixes

[flow-engine]
- Fixed the issue where the page got stuck when setting field values for a subform. (#9598) by gchust
- Fixed an issue where the popup displayed outdated UI data after toggling the UI configuration mode switch. (#9525) by gchust
[client]
- Fixed incorrect record action linkage rule behavior in table blocks. (#9652) by gchust
- Fixed the issue where selected relation field data was not displayed on mobile. (#9665) by zhangzhonghe
- Fixed the issue where fields became read-only when shown again after being hidden by linkage rules. (#9649) by katherinehhh
[cli] Fixed the nginx template to serve .mjs assets with the JavaScript MIME type. (#9626) by mytharcher
[database] Fixed an issue where importing numeric password values could fail. (#9635) by 2013xile
[AI employees] Fixed AI provider base URL validation. (#9667) by cgyrock
[Flow engine]
- Fixed an issue where dragging popup tabs to reorder them did not work. (#9602) by gchust
- Fixed an issue where modifying a block after duplicating its template could inadvertently affect the original block’s content. (#9664) by gchust
[Notification: In-app message] Fixed an SQL injection risk in the in-app notification channel timestamp filter. (#9630) by mytharcher
[License settings] Fixed the issue where the license settings page could hang for a long time when the pkg login check was slow or unreachable. (#9650) by hongboji
[Workflow: JavaScript] Clarified that Workflow JavaScript module support mode is unsafe and not a permission boundary. (#9629) by mytharcher

Reference: Workflow JavaScript
[Access control] Fixed incomplete permissions on first login when a union role was the default role. (#9632) by 2013xile
[File manager] Fixed local file storage path validation to prevent unsafe paths from escaping the configured storage root. (#9628) by mytharcher
[Password policy] Fixed an issue where password policy validation could fail for numeric password values. by 2013xile

v2.0.60

Release date: 2026-05-29

🚀 Improvements

[AI employees] Improved the LLM Base URL field so it can use global-scope variables in create and edit forms. (#9615) by cgyrock

🐛 Bug Fixes

[client] Fix the badge width in the top navigation bar (#9607) by zhangzhonghe
[AI employees] Fixed AI shortcut buttons getting an empty block context after referenced table blocks are removed. (#9617) by cgyrock
[Migration manager] Fix PostgreSQL migration diffs so child inherited columns are not dropped when a local column becomes inherited. by hongboji

v2.0.59

Release date: 2026-05-28

🐛 Bug Fixes

[ai] Pinned LangChain dependencies to stable versions to prevent Ollama model tool call failures and avoid affected upstream releases. (#9604) by cgyrock
[flow-engine] Fixed the incorrect frontend log level. (#9577) by gchust
[Collection: Tree] Fixed unclear error messages when queries failed due to circular parent-child relationships in tree data. (#9603) by zhangzhonghe
[AI: Knowledge base] Pinned LangChain dependencies to stable versions to prevent Ollama model tool call failures and avoid affected upstream releases. by cgyrock

v2.1.0-beta.44

Release date: 2026-06-03

🚀 Improvements

[Workflow: Approval] Adjusted validation rules for approval trigger and node configurations to ensure UI-related fields exist. by mytharcher

🐛 Bug Fixes

[client] Fixed the issue where selected relation field data was not displayed on mobile. (#9665) by zhangzhonghe
[client-v2]
- Fixed menu linkage rule save errors. (#9666) by zhangzhonghe
- Fixed excessive spacing above blocks on v2 pages. (#9647) by zhangzhonghe
[flow-engine] Fixed the issue where the page got stuck when setting field values for a subform. (#9598) by gchust
[AI employees]
- Fixed AI provider base URL validation. (#9667) by cgyrock
- Fixed ctx.get errors in AI employee workflow nodes. (#9661) by cgyrock
[Notification: In-app message] Fixed an SQL injection risk in the in-app notification channel timestamp filter. (#9630) by mytharcher
[Action: Duplicate record] Fixed the issue where the button state was not reset when duplicate record submission failed. (#9676) by katherinehhh
[Calendar] Fixed the issue where calendar event colors were not rendered from the configured color field in v2 pages. (#9677) by jiannx
[Flow engine]
- Fixed an issue where modifying a block after duplicating its template could inadvertently affect the original block’s content. (#9664) by gchust
- Fixed an issue where dragging popup tabs to reorder them did not work. (#9602) by gchust

v2.1.0-beta.43

Release date: 2026-06-02

🎉 New Features

[client-v2] Add TypedVariableInput so v2 email plugin's SMTP port and secure mode fields can accept either a typed constant or a {{ $env.X }} variable. (#9637) by Molunerfinn
[Access control] Migrated the Users and Roles & Permissions settings pages to v2. (#9619) by jiannx

🚀 Improvements

[undefined] Update the Embed NocoBase documentation for the open source plugin (#9642) by zhangzhonghe Reference: Embed NocoBase
[client] Enhanced autocomplete support for some built-in RunJS functions. (#9481) by gchust
[cli] improve init and self update guidance (#9633) by chenos

🐛 Bug Fixes

[client]
- Fix the issue where blocks may incorrectly show as deleted after refreshing the page (#9662) by zhangzhonghe
- Fixed incorrect record action linkage rule behavior in table block. (#9652) by gchust
- （linkage rule） fix fields becoming readonly when shown after being hidden (#9649) by katherinehhh
[cli] Fix nginx template to serve .mjs assets with JavaScript MIME type. (#9626) by mytharcher
[database] Fixed an issue where importing numeric password values could fail (#9635) by 2013xile
[flow-engine]
- Fixed an issue where the popup displayed outdated UI data after toggling the UI configuration mode switch. (#9525) by gchust
- Fix the issue where field search is cleared when hovering over association fields (#9646) by zhangzhonghe
[client-v2] preserve assign field values (#9640) by katherinehhh
[File manager] Fixed local file storage path validation to prevent unsafe paths from escaping the configured storage root. (#9628) by mytharcher
[Block: Gantt] Improved gantt tooltip placement to avoid covering task bars and aligned task labels consistently inside and outside bars (#9638) by jiannx
[Access control] Fixed incomplete permissions on first login when union role is the default (#9632) by 2013xile
[License settings] Fixed the license settings page hanging for a long time when the pkg login check is slow or unreachable (#9650) by hongboji
[Workflow: JavaScript] Clarify that Workflow JavaScript module support mode is unsafe and not a permission boundary (#9629) by mytharcher

Reference: Workflow JavaScript
[Password policy] Fixed an issue where password policy validation could fail for numeric password values by 2013xile

v2.1.0-beta.40

Release date: 2026-05-30

🎉 New Features

[client-v2] Support field value assignment in submit form actions (#9570) by katherinehhh
[Office File Previewer] Migrate the Office file preview plugin to the v2 (FlowEngine) client. (#9620) by Molunerfinn

🚀 Improvements

[Notification manager] Migrate the notification-related plugins to v2. (#9597) by Molunerfinn

🐛 Bug Fixes

[client] Fix the badge width in the top navigation bar (#9607) by zhangzhonghe
[Block: Gantt] Fixed the v2 gantt shared folder path and added zebra striping. (#9621) by jiannx
[License settings] Added client-v2 support for license settings and commercial license injection. (#9555) by jiannx
[Workflow: Custom action event] Fix duplicate Trigger workflow options in v2 block action menus (#9622) by zhangzhonghe
[AI employees] Fixed AI shortcut buttons getting an empty block context after referenced table blocks are removed. (#9617) by cgyrock
[plugin-commercial] Added client-v2 commercial license components and topbar license status entry. by jiannx
[Migration manager] Fix PostgreSQL migration diffs so child inherited columns are not dropped when a local column becomes inherited. by hongboji

v2.1.0-beta.38

Release date: 2026-05-29

🎉 New Features

[cli] Add dynamic API command compatibility guards (#9613) by chenos
[client-v2]
- Support embedded v2 pages and public form v2 pages (#9431) by zhangzhonghe
- Rewrite the client-v2 Plugin manager page into a responsive card-based UI with category filter, search, enable/disable/remove, Bulk enable, and a plugin detail modal; also make the client-v1 Plugin manager page responsive on narrow screens. (#9573) by Molunerfinn
[Workflow]
- Add timeout control for workflows, support to automatically abort timed-out execution if timeout option is set (#9363) by mytharcher
- Added an administrator API to rerun started workflow executions from the head or a specified node. (#9569) by mytharcher
[Block: Gantt] Added v2 support for the Gantt block. (#9545) by jiannx
[Workflow: Webhook] Add 408 response status for timed-out webhook workflow (sync mode) by mytharcher
[Workflow: Subflow] Support timeout setting in workflow by mytharcher
[Auth: OIDC] Migrate plugin-auth-oidc to v2 admin; sign-in button, admin settings form, and SSO auto-redirect now work under v2. by Molunerfinn
[Workflow: Approval] Support timeout setting in workflow by mytharcher
[Auth: LDAP] Add v2 client entry so the LDAP authenticator renders its sign-in form and admin settings on v2 apps. by Molunerfinn

🚀 Improvements

[client-v2]
- Add v2 table row selection setting (#9614) by katherinehhh
- Support action panel action colors (#9612) by katherinehhh
- Remove the Hidden option from menu configuration (#9596) by zhangzhonghe
[client] Remove the Hidden option from menu item settings (#9595) by zhangzhonghe
[cli] Streamline app upgrade flow (#9587) by chenos
[AI employees] Improved the LLM Base URL field so it can use global-scope variables in create and edit forms. (#9615) by cgyrock
[IP restriction] Add a v2 client for the IP restriction plugin. by Molunerfinn

🐛 Bug Fixes

[flow-engine]
- Fixed the incorrect frontend log level. (#9577) by gchust
- Fix unstable cascading menus when typing in search boxes (#9473) by zhangzhonghe
- Fixed an issue where table action linkage rules would execute incorrectly after a form was successfully submitted in a popup. (#9445) by gchust
[ai] Pinned LangChain dependencies to stable versions to prevent Ollama tool execution failures and avoid affected upstream releases (#9604) by cgyrock
[client-v2]
- Fix the sub-app sign-in tabs rendering raw translation templates, and prevent the v2 authentication-method edit drawer from dropping field values on submit. (#9581) by Molunerfinn
- Improve plugin manager page performance by using CSS line-clamp instead of antd Typography ellipsis. (#9593) by Molunerfinn
[client]
- Fix preserve time format for v2 time fields (#9579) by katherinehhh
- Fix sync hidden state for subform linkage (#9594) by katherinehhh
- Increase scan input image upload limit (#9580) by katherinehhh
- Fix sync mobile date picker popup value (#9582) by katherinehhh
- Fix page tabs disappearing after switching menus (#9583) by zhangzhonghe
- Fix issue where subtable in subform could not add a second row (#9586) by katherinehhh
- Increase scan input image upload limit (#9580) by katherinehhh
[Collection: Tree] Fix the error caused by circular parent-child data in tree collections (#9603) by zhangzhonghe
[Workflow: Custom action event]
- Fixed custom action table buttons with multiple records context incorrectly allowing custom context workflows to be selected. (#9608) by mytharcher
- Filter custom action workflow binding options by the current block collection. (#9610) by mytharcher
[File manager]
- Improved PDF preview failure messages and documented CORS requirements for external storage. (#9600) by mytharcher Reference: File Preview
- Fixed Unicode filename normalization during file uploads to avoid generating object keys with control characters. (#9584) by mytharcher
[AI: Knowledge base] Pinned LangChain dependencies to stable versions to prevent Ollama tool execution failures and avoid affected upstream releases by cgyrock
[Template print] Fixed template print PDF conversion errors not being returned to the client correctly by jiannx

develop

v2.1.0-alpha.45

Release date: 2026-05-29

🎉 New Features

[client-v2]
- Support field value assignment in submit form actions (#9570) by katherinehhh
- Support embedded v2 pages and public form v2 pages (#9431) by zhangzhonghe
- Add a Security menu and the Token policy settings page to the v2 admin; user-center now supports Change password. (#9556) by Molunerfinn
- Rewrite the client-v2 Plugin manager page into a responsive card-based UI with category filter, search, enable/disable/remove, Bulk enable, and a plugin detail modal; also make the client-v1 Plugin manager page responsive on narrow screens. (#9573) by Molunerfinn
[cli]
- Add dynamic API command compatibility guards (#9613) by chenos
- Support basic authentication (#9558) by chenos
[Office File Previewer] Migrate the Office file preview plugin to the v2 (FlowEngine) client. (#9620) by Molunerfinn
[Workflow]
- Add timeout control for workflows, support to automatically abort timed-out execution if timeout option is set (#9363) by mytharcher
- Added an administrator API to rerun started workflow executions from the head or a specified node. (#9569) by mytharcher
[IdP: OAuth] Added foundation support for app single sign-on in multi-app deployments (#9547) by 2013xile
[Block: Gantt] Added v2 support for the Gantt block. (#9545) by jiannx
[App SSO] Added an App SSO plugin for automatic sign-in between applications by 2013xile
[Password policy] Migrate plugin-password-policy to the client-v2 admin shell with the Password policy / Locked users settings pages and client-side rule enforcement on the user-center change-password form. by Molunerfinn
[Workflow: Webhook] Add 408 response status for timed-out webhook workflow (sync mode) by mytharcher
[Workflow: Subflow] Support timeout setting in workflow by mytharcher
[Auth: OIDC] Migrate plugin-auth-oidc to v2 admin; sign-in button, admin settings form, and SSO auto-redirect now work under v2. by Molunerfinn
[Workflow: Approval] Support timeout setting in workflow by mytharcher
[App supervisor] Added App SSO settings for sub applications by 2013xile
[Auth: LDAP] Add v2 client entry so the LDAP authenticator renders its sign-in form and admin settings on v2 apps. by Molunerfinn

🚀 Improvements

[client-v2]
- add v2 table row selection setting (#9614) by katherinehhh
- support action panel action colors (#9612) by katherinehhh
- Remove the Hidden option from menu configuration (#9596) by zhangzhonghe
[client] Remove the Hidden option from menu item settings (#9595) by zhangzhonghe
[cli] streamline app upgrade flow (#9587) by chenos
[Notification manager] Migrate the notification-related plugins to v2. (#9597) by Molunerfinn
[AI employees] Improved the LLM Base URL field so it can use global-scope variables in create and edit forms. (#9615) by cgyrock
[Workflow] Refactor workflow async-node availability checks (#9532) by mytharcher
[Data visualization] Added client v2 support for chart blocks. (#9517) by jiannx
[IP restriction] Add a v2 client for the IP restriction plugin. by Molunerfinn

🐛 Bug Fixes

[client]
- Fix the badge width in the top navigation bar (#9607) by zhangzhonghe
- Increase scan input image upload limit (#9580) by katherinehhh
- Fix page tabs disappearing after switching menus (#9583) by zhangzhonghe
- Fix issue where subtable in subform could not add a second row (#9586) by katherinehhh
- Fix preserve time format for v2 time fields (#9579) by katherinehhh
- Fix sync mobile date picker popup value (#9582) by katherinehhh
- Fix sync hidden state for subform linkage (#9594) by katherinehhh
[flow-engine]
- Fixed the incorrect frontend log level. (#9577) by gchust
- Fix unstable cascading menus when typing in search boxes (#9473) by zhangzhonghe
- Fixed an issue where table action linkage rules would execute incorrectly after a form was successfully submitted in a popup. (#9445) by gchust
[ai] Pinned LangChain dependencies to stable versions to prevent Ollama tool execution failures and avoid affected upstream releases (#9604) by cgyrock
[client-v2]
- Fix the sub-app sign-in tabs rendering raw translation templates, and prevent the v2 authentication-method edit drawer from dropping field values on submit. (#9581) by Molunerfinn
- Improve plugin manager page performance by using CSS line-clamp instead of antd Typography ellipsis. (#9593) by Molunerfinn
- Fixed browser language metadata so the app page follows the selected application language instead of being marked as English. (#9564) by Molunerfinn
[build]
- Text assets in server builds are now copied as files instead of being converted into JavaScript modules. (#9565) by Molunerfinn
- Fixed plugin server obfuscation output to avoid browser globals in Node.js runtime bundles. (#9559) by Molunerfinn
[Block: Gantt] Fixed the v2 gantt shared folder path and added zebra striping. (#9621) by jiannx
[License settings] Added client-v2 support for license settings and commercial license injection. (#9555) by jiannx
[Workflow: Custom action event]
- Fix duplicate Trigger workflow options in v2 block action menus (#9622) by zhangzhonghe
- Filter custom action workflow binding options by the current block collection. (#9610) by mytharcher
- Fixed custom action table buttons with multiple records context incorrectly allowing custom context workflows to be selected. (#9608) by mytharcher
[Collection: Tree] Fix the error caused by circular parent-child data in tree collections (#9603) by zhangzhonghe
[File manager]
- Improved PDF preview failure messages and documented CORS requirements for external storage. (#9600) by mytharcher Reference: File Preview
- Safely render PDF previews with PDF.js instead of iframe-based raw PDF rendering. (#9566) by mytharcher
- Fixed Unicode filename normalization during file uploads to avoid generating object keys with control characters. (#9584) by mytharcher
[AI employees]
- Fixed AI shortcut buttons getting an empty block context after referenced table blocks are removed. (#9617) by cgyrock
- fixed incorrect description of the tool name in the work context prompt (#9567) by cgyrock
[Workflow: Manual node] Fixed temporary saves for manual workflow tasks not persisting submitted form values. (#9554) by mytharcher
[plugin-commercial] Added client-v2 commercial license components and topbar license status entry. by jiannx
[AI: Knowledge base] Pinned LangChain dependencies to stable versions to prevent Ollama tool execution failures and avoid affected upstream releases by cgyrock
[Migration manager] Fix PostgreSQL migration diffs so child inherited columns are not dropped when a local column becomes inherited. by hongboji
[Template print] Fixed template print PDF conversion errors not being returned to the client correctly by jiannx
[Auth: OIDC] Fixed token leakage when SSO login callbacks receive an external redirect URL by 2013xile
[Workflow: Approval]
- Fix the issue where jobs:resume API is not supported by approval node by mytharcher
- Fixed approval withdraw to update submitted business data while respecting source collection update permissions. by mytharcher
- Fixed stale approval todos when approval workflows are terminated by non-approval node failures. by mytharcher

Top 6 Open Source AI Tools by GitHub Stars for Stronger AI Agents

NocoBase — Wed, 03 Jun 2026 16:48:50 +0000

Originally published at https://www.nocobase.com/en/blog/6-github-top-open-source-ai-tools-for-ai-agents

Introduction

Over the past year, the number of open source AI tools has grown rapidly. On GitHub, the ai-tools topic has already gathered a large number of projects.

We found that many popular open source AI tools are designed to enhance the capabilities of existing AI systems and AI Agents.

They work like capability boosters for AI Agents: some help Agents operate webpages, some make Agents better at writing code, some allow Agents to call external tools, some make AI output more stable, and some help AI work inside real business systems.

So, in this article, we start from the most popular open source projects under GitHub’s ai-tools topic. Based on GitHub Stars, we will look at 6 of the most popular open source AI tools today and explain which AI capabilities they enhance.

How did we select these tools?

To keep this article as objective as possible, we selected the tools based on publicly available GitHub data.

This selection mainly follows these rules:

Data source: GitHub Topics ai-tools
Sorting method: Based on GitHub Stars, shown from rank 6 to rank 1

Rank	Tool	GitHub Stars	Main direction	Best suited for
6	NocoBase	22.6k	AI-powered no-code business systems	Building enterprise internal systems such as CRM, approval, ticketing, and operations backends
5	OpenCLI	23.4k	AI tool interface / CLI	Packaging websites, local tools, or browser sessions into commands that AI Agents can call
4	OpenClaude	28.3k	AI Coding Agent	Using a multi-model AI Coding Agent in the terminal
3	prompt-optimizer	30.3k	Prompt optimization	Optimizing, testing, and reusing prompts
2	cc-switch	90k	AI Coding tool management	Managing configurations for AI Coding tools such as Claude Code, Codex, and OpenCode
1	browser-use	96.8k	Browser automation / AI Agent	Letting AI operate webpages and complete browser tasks

Data collected on June 3, 2026. Since GitHub Stars change over time, the actual numbers may be slightly different when you read this article.

NocoBase

Website: https://www.nocobase.com/

Online Demo: demo.nocobase.com/new

Documentation: docs.nocobase.com

GitHub: https://github.com/nocobase/nocobase

GitHub Stars: 22.6k

First open-sourced: 2021

License: Apache-2.0

Project introduction

NocoBase is an open source AI-powered no-code platform for quickly building enterprise internal business systems.

In NocoBase, AI can directly participate in application building. You can describe your business requirements in natural language and let AI help create data models, configure pages, orchestrate workflows, and even assist with plugin development.

This means AI is not simply generating a pile of code from scratch. Instead, it builds systems inside a platform that already has data models, pages, permissions, workflows, and a plugin system. After generation, users can continue checking, adjusting, and maintaining the system through NocoBase’s no-code interface.

What problem does it solve?

“How can AI build business systems inside a structured platform, instead of temporarily generating code in an empty project?”

In NocoBase, AI can work with the platform’s existing business system capabilities, including data models, page building, permission control, workflows, plugin extensions, and AI Employees. This lets AI speed up system building, while humans confirm business logic, adjust details, and control boundaries.

For enterprise internal systems, this approach is more reliable. It preserves AI efficiency while avoiding the maintenance problems that often come with generating code completely from scratch.

Best way to use it

NocoBase is best suited for building enterprise internal systems with clear structures and long-term iteration needs.

A better way to use it is:

Start with a specific business scenario

Do not begin by asking AI to “build me a complete ERP.” A better approach is to start with a specific scenario, such as customer management, purchase requests, equipment ledgers, after-sales tickets, contract approval, or project dashboards.

Use natural language to let AI build the system foundation

You can first describe the business objects, field relationships, page requirements, and workflow rules, then let AI create data models, configure pages, and orchestrate workflows in NocoBase. For example:

Help me build a customer management system, including customers, contacts, opportunities, and follow-up records. A customer can be linked to multiple contacts and opportunities. Each opportunity should include stage, amount, expected closing date, and owner.

Check and adjust in the no-code interface

After AI generates the system, do not treat it as the final version right away. Go into NocoBase’s visual interface and check whether the data tables, fields, relationships, page layouts, action buttons, and permission configurations match the real business needs.

Configure permissions and workflow boundaries

For internal systems, permissions and workflows are not optional. Different roles should see different data and perform different actions. Workflows involving approvals, notifications, status changes, and data validation should also have clear rules.

Let AI participate in system operations

After the system is built, AI can continue participating in business operations. For example, AI Employees can help with data analysis, report generation, translation, decision support, form filling, workflow node processing, and more.

Keep iterating instead of generating once

The strength of NocoBase is not “generate everything once.” After AI builds the system, teams can still adjust fields, pages, workflows, and permissions in a no-code way. This makes it more suitable for the long-term changes of real business systems.

Suitable scenarios

NocoBase is suitable for these scenarios:

CRM customer management systems
Approval systems
Ticketing systems
Project management systems
Lightweight ERP modules such as procurement, inventory, and orders
Operations backends and admin backends
Equipment management, asset management, and archive management
Customer follow-up and service management
Enterprise internal systems that require private deployment
Business applications that require permissions, workflows, data models, and continuous iteration
Teams that want to build systems with AI and no-code together

Usage boundaries

NocoBase’s core strength is business system building, but it is not suitable for every AI tool scenario.

Important boundaries include:

Not ideal for one-off web pages: If you only want to quickly generate a simple display page, campaign page, or one-off demo, NocoBase is not the most direct choice. It is better suited for business systems with data models, permissions, workflows, and long-term maintenance needs.
Not a full replacement for professional development frameworks: If you need highly customized frontend interactions, complex consumer-facing products, or internet applications for massive user bases, traditional development frameworks are still more suitable.
Business modeling is still needed upfront: NocoBase can speed up system building, but users still need to understand their business objects, data relationships, and workflow boundaries. If the data model is poorly designed, the system will become more complex later.
Complex customization still requires development skills: Although many functions can be configured without code, deep plugin development, complex integrations, and special business logic still require developers.

More precisely, NocoBase is suitable for building maintainable, extensible, and governable business systems. It is not meant to replace all AI tools. Instead, it provides a stable system foundation for AI to enter real business workflows.

Installation Prompt

You can copy the following Prompt to Claude Code, Cursor, Codex, OpenCode, or other AI Coding Agents:

Please help me install and initialize NocoBase locally.

Requirements:
1. Open the official GitHub repository:
   https://github.com/nocobase/nocobase

2. Read the official README and follow the AI Agent Access quickstart.

3. Check whether Node.js and npm are installed.

4. Install the NocoBase CLI beta version:
   npm install -g @nocobase/cli@beta

5. Create a new project directory:
   mkdir my-nocobase && cd my-nocobase

6. Initialize NocoBase with UI:
   nb init --ui

7. After initialization, explain what files and directories were created.

8. Start or restart the AI agent session inside this directory.
   For example:
   cd my-nocobase && codex

OpenCLI

Website: https://opencli.info/

GitHub: https://github.com/jackwener/OpenCLI

GitHub Stars: 23.4k

First open-sourced: March 2026

License: Apache-2.0

Project introduction

OpenCLI is an open source project that converts websites, browser sessions, Electron apps, and local tools into CLI interfaces. It can turn GUI-based tools into more predictable command-line interfaces, so both humans and AI Agents can complete actions through commands.

For example, it can package website capabilities into commands:

opencli hackernews top --limit 5
opencli bilibili hot --limit 5

It can also let AI Agents use opencli browser to operate Chrome pages where the user is already logged in, completing actions such as opening webpages, reading pages, clicking buttons, filling out forms, and extracting data.

Suitable scenarios

OpenCLI is suitable for these scenarios:

Turning common website capabilities into CLI commands
Letting AI Agents operate logged-in Chrome pages
Providing more stable external tool interfaces for Agents
Packaging operations for content platforms, community platforms, job sites, and social platforms
Extracting structured data from webpages
Registering local CLI tools for Agents to use
Creating adapters for repetitive web tasks
Letting tools such as Claude Code and Cursor call external website capabilities

Installation Prompt

You can copy the following Prompt to Claude Code, Cursor, Codex, or other AI Coding Agents:

Please help me install and configure OpenCLI locally.

Requirements:
1. Check whether Node.js >= 20 is installed.
2. Install OpenCLI using the official command:
   npm install -g @jackwener/opencli

3. Verify the installation:
   opencli --version

4. Install the OpenCLI Browser Bridge extension for Chrome.
   Prefer the Chrome Web Store installation if available.
   If not, guide me to install it manually from GitHub Releases.

5. Run the environment check:
   opencli doctor

6. If I have multiple Chrome profiles, help me list and rename them:
   opencli profile list
   opencli profile rename  work
   opencli profile use work

7. Run a simple test command:
   opencli list
   opencli hackernews top --limit 5

8. Explain what each step does.

9. Do not access private pages, send messages, publish content, delete data, or submit forms during the initial test.

10. After setup, explain:
   - How OpenCLI connects to Chrome
   - Where OpenCLI stores local configuration
   - How to safely use it with AI agents
   - What actions should require manual confirmation

OpenClaude

Website: https://openclaude.gitlawb.com/

GitHub: https://github.com/Gitlawb/openclaude

GitHub Stars: 28.3k

First open-sourced: March 2026

License: Custom license

Project introduction

OpenClaude is an open source AI Coding Agent CLI. It lets developers use different models and service providers in the terminal to complete code-related tasks, instead of being locked into a single model or a closed tool.

OpenClaude supports multiple model backends, including OpenAI-compatible APIs, Gemini, GitHub Models, Codex, Ollama, Atomic Chat, and more. It also supports common coding agent capabilities, such as reading files, modifying files, running Bash commands, searching code, calling tools, using MCP, executing slash commands, and streaming output.

Best way to use it

OpenClaude is best suited for developers who are already used to terminal-based development and want more flexibility when using different models.

Suitable scenarios

Using an AI Coding Agent in the terminal
Using different models to handle coding tasks
Letting AI understand and modify local codebases
Using AI to generate tests, documentation, and refactoring suggestions
Testing different backends such as OpenAI-compatible APIs, Gemini, Codex, and Ollama
Combining MCP, Bash, file tools, and code search
Building a more open AI coding workflow
Comparing how different models perform on coding tasks

More precisely, OpenClaude is suitable as an AI coding workspace for developers. It helps you use different models more flexibly for coding tasks, but it still requires developers to provide clear goals, review results, and control execution risks.

Installation Prompt

You can copy the following Prompt to Claude Code, Cursor, Codex, or other AI Coding Agents:

Please help me install and configure OpenClaude locally.

Requirements:
1. Check whether Node.js and npm are installed.
2. Install OpenClaude globally using the official command:
   npm install -g @gitlawb/openclaude@latest

3. Verify the installation:
   openclaude --version

4. Start OpenClaude:
   openclaude

5. Help me configure one model provider.
   Prefer OpenAI-compatible setup first.

6. Use environment variables for API keys.
   Do not hardcode or print any API key.

7. If I want to use a local model, help me check whether Ollama is installed.
   If Ollama is available, configure OpenClaude with:
   OPENAI_BASE_URL=http://localhost:11434/v1
   OPENAI_MODEL=qwen2.5-coder:7b

8. Create a small test task:
   - Open a simple local project
   - Ask OpenClaude to explain the project structure
   - Ask it to suggest one small improvement
   - Do not allow it to modify files until I confirm

9. After the test, explain:
   - Which provider is currently active
   - Where the configuration is stored
   - How to switch providers later
   - How to safely review file changes

Prompt Optimizer

Website: always200.com

GitHub: https://github.com/linshenkx/prompt-optimizer

GitHub Stars: 30.3k

First open-sourced: February 2025

License: Custom license

Project introduction

Prompt Optimizer is an open source prompt optimization tool that helps users write prompts that are clearer, more stable, and easier to reuse.

Best way to use it

Prompt Optimizer is best suited for AI use cases that are high-frequency, reusable, and have requirements for output quality. It is especially useful for content creation, AI application development, customer service replies, coding assistance, image generation, data analysis explanations, knowledge base Q&A, and similar scenarios.

Installation Prompt

If you just want to try it quickly, you can use the online version directly.

If you want to deploy it locally or use it privately, you can copy the following Prompt to Claude Code, Cursor, Codex, or other AI Coding Agents:

Please help me deploy Prompt Optimizer locally.

Requirements:
1. Open the official GitHub repository:
   https://github.com/linshenkx/prompt-optimizer

2. Read the official README and choose the simplest local deployment method.

3. Prefer Docker deployment if Docker is installed:
   docker run -d -p 8081:80 --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizer

4. If Docker is not installed, help me check whether Node.js and pnpm are available, then guide me through local development setup.

5. After deployment, open the web interface at:
   http://localhost:8081

6. Help me configure at least one AI model provider, such as OpenAI, Gemini, DeepSeek, or a custom OpenAI-compatible API.

7. Do not print or hardcode any API key in the terminal or source code.

8. Explain where the configuration is stored and how to update or remove API keys later.

9. Create a simple test:
   - Input a short prompt: "Help me write a product update email"
   - Optimize it
   - Compare the original and optimized prompt
   - Explain why the optimized version is better or worse

10. Make sure the final setup can be reused later.

CC Switch

Website: https://ccswitch.io

GitHub: https://github.com/farion1231/cc-switch

GitHub Stars: 90k

First open-sourced: August 2025

License: MIT

Project introduction

CC Switch is a cross-platform desktop tool for centrally managing model providers, API Keys, MCP, prompts, and Skills configurations across multiple AI Coding / AI CLI tools.

It supports tools including Claude Code, Claude Desktop, Codex, Gemini CLI, OpenCode, OpenClaw, and Hermes.

CC Switch centralizes scattered configurations into one desktop app, allowing developers to manage and switch them through a graphical interface instead of repeatedly editing JSON, TOML, or .env files by hand.

Best way to use it

CC Switch is best suited for heavy users of AI Coding tools, especially developers who already use multiple CLI tools, multiple model providers, or multiple API Keys at the same time.

CC Switch is suitable for these scenarios:

Using multiple AI Coding tools at the same time
Frequently switching between tools such as Claude Code, Codex, Gemini CLI, and OpenCode
Managing multiple model providers and API Keys
Reducing the risk of manually editing configuration files
Centrally managing MCP, prompts, and Skills
Syncing AI tool configurations across multiple devices
Managing AI Coding workflows through a desktop interface

Installation Prompt

You can copy the following Prompt directly to Claude Code, Cursor, Codex, or other AI Coding Agents:

Please help me install and configure CC Switch on my local machine.

Requirements:
1. Detect my operating system: macOS, Windows, or Linux.
2. Follow the official installation method from the CC Switch GitHub repository.
3. If I am on macOS, prefer installing via Homebrew:
   brew install --cask cc-switch
4. If I am on Windows or Linux, guide me to download the correct installer from GitHub Releases.
5. After installation, help me launch CC Switch.
6. Check whether my existing AI CLI tools are installed, such as Claude Code, Codex, Gemini CLI, OpenCode, or OpenClaw.
7. Help me import the existing configuration if available.
8. Create one test Provider configuration.
9. Explain where CC Switch stores its local data and backups.
10. Do not expose or print any API key in the terminal output.

Official GitHub repository:
farion1231/cc-switch

Official website:
ccswitch.io

browser-use

Official website: https://browser-use.com/
GitHub: https://github.com/browser-use/browser-use
GitHub Stars: 96.8k
First open-sourced: November 2024
License: MIT

Project introduction

browser-use is an open source tool that lets AI Agents operate browsers.

Most websites were originally designed for humans, not for AI Agents. If AI wants to complete web tasks, it usually needs to understand page content, identify buttons and input fields, click elements, fill out forms, navigate between pages, and even handle multi-step workflows.

browser-use can turn the browser into an execution environment for AI Agents, allowing AI to complete tasks on webpages like a human.

Best way to use it

browser-use works best as part of an AI Agent toolchain, rather than as a complete standalone product.

A better way to use it is:

Define a very specific web task first

For example: log in to a backend system, find orders from the past 7 days, and export the results.

Let the AI Agent use browser-use to operate the web

browser-use handles opening pages, identifying elements, clicking buttons, filling in content, and reading webpage states.

Add restrictions and checks for key workflows

For example, do not let AI submit payments, delete data, or modify production environment configurations without control. For high-risk actions, it is best to add human confirmation.

Turn stable scenarios into automated workflows

For highly repetitive web tasks, successful workflows can be saved and then gradually optimized.

Prioritize browser stability in production environments

If a task involves high concurrency, proxies, CAPTCHAs, browser fingerprints, or login state management, you should consider not only local execution but also cloud browsers or hosted environments.

browser-use is suitable for these scenarios:

AI Agent browser automation
Web form filling
Automated operation of backend systems
Data collection and information queries
Simulating human web operations
Testing AI Agents’ ability to perform tasks on the web
Adding browser action capabilities to existing Agents

Installation Prompt

You can copy the following Prompt directly to Claude Code, Cursor, Codex, or other AI Coding Agents:

Please help me install and run browser-use locally.

Requirements:
1. Check whether Python 3.11 or above is installed.
2. Use uv to create a clean Python environment.
3. Install browser-use.
4. Install Chromium if it is not available.
5. Create a simple example script that uses browser-use to open a webpage and complete a basic task.
6. Use an environment variable for the LLM API key. Do not hardcode the API key in the script.
7. Add clear comments so I can understand each step.
8. After installation, run the example and help me verify whether browser-use works correctly.

Official GitHub repository:
browser-use/browser-use

Please follow the official quickstart as much as possible.

If you want to test a simple task directly, you can change the task to:

Create a browser-use example that opens the browser-use GitHub repository, finds the current number of GitHub stars, and prints the result.

FAQ

Are these open source AI tools suitable for enterprise use?

It depends on the specific tool and use case.

Tools like browser-use and OpenCLI are better suited for Agent automation and external tool calling. NocoBase is better suited for building enterprise internal business systems.

What is the difference between browser-use and OpenCLI?

Both can enhance an AI Agent’s ability to operate webpages and external tools, but they do it in different ways.

browser-use is more like letting AI directly operate the browser. AI opens webpages, reads pages, clicks buttons, fills out forms, and decides the next step based on the page state.

OpenCLI focuses more on packaging websites, local tools, or browser sessions into CLI commands. This allows AI Agents to call tools through commands instead of starting from the webpage interface every time.

If I want to build enterprise internal systems, what type of AI tool should I choose?

If your goal is to build enterprise internal systems such as CRM, approval systems, ticketing systems, project management, and operations backends, AI Coding tools alone are usually not enough.

These systems often require data models, permission control, page configuration, workflows, private deployment, and ongoing maintenance. AI can help speed up system building, but the system itself still needs a stable business application foundation.

This is where platforms like NocoBase fit well. It does not simply let AI generate code. Instead, it lets AI build maintainable business systems based on data models, pages, permissions, and workflows.

Summary

In the past, we paid more attention to “what AI can generate.” But in real workflows, the more important questions are: Can AI operate real tools? Can it call external systems? Can it enter business workflows? Can the generated result continue to be maintained?

This is exactly the value of these open source AI tools.

Related reading

5 Open-Source Internal Tools to Use with Hermes Agent

NocoBase — Sat, 30 May 2026 12:48:15 +0000

Originally published at https://www.nocobase.com/en/blog/open-source-internal-tools-self-hosted-ai-agent-hermes

AI Agents are no longer only popular in development scenarios.

Besides tools like Claude Code and OpenClaw, Hermes Agent has also started getting more attention recently.

On Reddit, one user mentioned that after trying several Agent tools, including OpenClaw, Nanobot, and Nanoclaw, they still preferred Hermes Agent in the end. It keeps the capabilities they actually need without unnecessary overhead. For scenarios such as local models, self-hosted servers, SSH access, and Telegram-based operations, it also fits a lighter and more controllable setup.

💡Read more:

How can OpenClaw be used in real business? 5 recommended open source tools

After using Claude Code, you need these 6 open source tools

For teams that are already planning to build self-hosted business systems or internal tools, Hermes Agent is a strong fit if the AI Agent needs to be used inside real business systems to handle data queries, system configuration, workflow maintenance, and task execution.

The internal tool platform provides the foundation for the business system, while Hermes works as a self-hosted Agent that helps teams query, configure, and maintain systems with natural language, and capture repeatable operations as reusable Skills.

This article focuses on internal tool platforms such as NocoBase, Appsmith, Budibase, Directus, and Baserow, and explains how they can be used with Hermes Agent in different scenarios.

First, here is a table of the tools covered in this article, the common business systems they are suited for, and the capabilities Hermes Agent can add.

Tool	Recommended business systems / internal tools	What Hermes Agent can add
NocoBase	CRM, ERP, approval systems, ticketing systems, project management, supplier management, asset management, operations backends, and other business systems	Use natural language to plan data models, configure pages and permissions, maintain workflows, and capture high-frequency business modules as reusable Skills
Appsmith	Admin panels, data dashboards, customer service backends, review panels, operations tools, database management interfaces	Clarify page structures, organize query and filter logic, explain relationships between components and data sources, and reuse common admin page templates
Budibase	Form systems, approval workflows, employee requests, IT service desks, operations workflow apps, internal workflow tools	Clarify form fields, approval nodes, and status transitions, generate workflow templates, and capture request handling Skills
Directus	Database backends, API management, content management systems, structured data management platforms, data operations backends	Explain data structures, organize field relationships, support natural language queries, and capture data management and content maintenance workflows
Baserow	Table-based databases, lightweight CRM, supplier lists, content plans, project progress tables, inventory lists	Plan table structures and views, organize filter rules, generate category and status fields, and reuse lightweight app templates

1. NocoBase

Official website: https://www.nocobase.com/

GitHub: https://github.com/nocobase/nocobase

GitHub Star: 22.6k

Introduction

NocoBase is an open source AI no-code / low-code platform for building enterprise internal business systems and admin backends.

At its core, NocoBase helps teams build long-running business systems through data models, page configuration, permission management, workflows, and plugin extensions. These systems usually change over time: fields need to be adjusted, pages need to be optimized, permissions need to be redefined, and approval and notification workflows need to be updated as the business changes.

NocoBase is well suited for these long-term systems, while Hermes Agent can further participate in system building, configuration, and maintenance.

In terms of AI capabilities, NocoBase already provides AI Employees, AI Skills, CLI, MCP, and related support. AI Employees can act as intelligent assistants inside the system and help with data queries, content generation, task handling, and more. AI Skills help external Agents understand how NocoBase is configured and what they can and cannot operate on. The CLI lets Agents execute installation, creation, modification, and other operations through commands. MCP provides a more standard entry point for external AI tools to connect to NocoBase.

What can it do with Hermes?

After Hermes is connected to NocoBase, it can understand the NocoBase configuration system through NocoBase Skills and execute creation, modification, deployment, and other operations through the NocoBase CLI.

1. Create business modules with natural language

For example, when creating a customer renewal management module, you can first let Hermes organize the data structures for customers, contracts, renewal records, follow-up tasks, and more. Then it can plan the list pages, detail pages, dashboards, and basic permissions.

2. Help maintain permissions and workflows

For example, if the rule is “sales can only view the customers they own, supervisors can view their team’s customers, and finance can view contract amounts,” Hermes can turn this business description into more specific permission and workflow configuration logic.

3. Capture high-frequency operations as Skills

After completing a CRM, approval workflow, or supplier management module for the first time, Hermes can capture practices such as field naming, page structure, and permission rules. These can then be reused when building similar modules later.

Task instruction example

Help me create a customer renewal management module in NocoBase.

It needs to include customer information, contract expiration date, renewal status, owner, follow-up records, and an approval workflow.

For permissions:
Sales can only view customers they own.
Sales supervisors can view team customers.
Finance can view contract amounts and payment status.
Administrators can view and edit all content.

For workflows:
Automatically generate a renewal reminder 30 days before the contract expires.
When the renewal amount exceeds 100,000 yuan, supervisor and finance approval is required.
After approval, update the renewal status and generate the next follow-up task.

After completion, please organize this module building process into a reusable Skill, so it can be used later to create supplier management, contract management, or project management modules.

Related resources

Documentation: https://docs.nocobase.com/

AI documentation: https://docs.nocobase.com/en/ai/

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

Hermes Agent: https://docs.nocobase.com/en/ai/hermes-agent

2. Appsmith

Official website: https://www.appsmith.com/

GitHub: https://github.com/appsmithorg/appsmith

GitHub Star: 39.9k

Introduction

Appsmith is an open source low-code platform mainly used to build internal apps such as admin panels, data dashboards, customer support backends, review tools, and IT tools. It can connect to databases, APIs, and third-party services, and quickly build interfaces for internal teams through drag-and-drop components, query configuration, and JavaScript extensions.

Appsmith provides Appsmith AI, which can add AI queries, text generation, classification, summarization, and other capabilities to applications. It can also build AI interactions around internal data. Appsmith is also developing Appsmith Agents to bring AI capabilities into the tools and systems teams use every day.

What can it do with Hermes?

Appsmith builds specific pages and data operation interfaces, while Hermes helps teams turn natural language requirements into clearer page structures, query logic, and operation rules.

Plan internal admin interfaces

For example, when building an order exception handling panel, you can first ask Hermes to clarify which fields should be displayed, which filters are needed, which action buttons are required, and how the page should be divided into sections. Appsmith can then handle the specific interface building and data connection.

Organize query and filter logic

A common issue with internal tools is not whether a page exists, but whether the data logic behind the page is clear. Hermes can help teams turn descriptions such as “which orders do I want to see,” “how should exceptions be identified,” and “which records should be prioritized” into query conditions and operation rules.

Capture admin page templates

Customer support backends, review panels, operations dashboards, and finance query pages often appear repeatedly. Hermes can capture common fields, component layouts, filters, and operation logic as Skills, so similar pages can be reused later.

Task instruction example

Help me plan an order exception handling panel, which will later be built in Appsmith.

The page needs to display abnormal orders, customer names, order amounts, owners, exception reasons, processing status, and the most recent communication record.

Filters include:
Region.
Order amount.
Processing status.
Owner.
Exception type.

For operations:
Operations staff can update the processing status.
Supervisors can assign owners in batches.
Finance can only view order amounts and payment status.

Please organize the page structure, data query logic, and component layout, and capture them as a reusable internal tool page template.

Related resources

Documentation: https://docs.appsmith.com/

Appsmith AI: https://docs.appsmith.com/connect-data/reference/appsmith-ai

3. Budibase

Official website: https://budibase.com/

GitHub: https://github.com/Budibase/budibase

GitHub Star: 28k

Introduction

Budibase is an open source operations platform mainly used to build internal apps, automation workflows, and AI Agents. It is more focused on process-based business scenarios, such as employee requests, approval handling, IT service desks, form routing, data updates, and operations automation.

Budibase supports generating code, generating database tables, and creating automation workflows powered by large language models. Budibase Agents are also being developed, allowing teams to define Agent behavior through natural language and connect it to internal data and APIs.

What can it do with Hermes?

Budibase is better suited for forms, approvals, and workflow-based applications. Hermes can help teams clarify rules in the early stage of workflow design and capture high-frequency request handling methods later.

Clarify forms and approval workflows

For processes such as equipment requests, expense reimbursement, customer support, and contract approval, Hermes can first help teams break down fields, approval nodes, trigger conditions, and notification rules. Budibase can then handle the actual application building.

Generate workflow handling templates

Many internal requests follow fixed handling patterns. Hermes can organize workflows such as “employee submits a request, supervisor approves it, the relevant department handles it, status is updated, and the applicant is notified” into templates for quick reuse later.

Capture operations rules

Workflow-based applications often need to change as organizational rules change. Hermes can record approval sequences, exception handling methods, role responsibilities, and notification rules, turning them into reusable Skills.

Task instruction example

Help me design an employee equipment request process, which will later be built in Budibase.

The process includes:
The employee submits an equipment request.
The supervisor approves it.
IT confirms inventory.
After approval, the equipment status is updated.
The system notifies the applicant to collect the equipment.

The form fields include:
Applicant.
Department.
Equipment type.
Purpose description.
Expected collection time.
Approval status.
Handler.

Please organize the form fields, approval nodes, status transitions, and notification rules, and capture this equipment request process as a reusable Skill.

Related resources

Documentation: https://docs.budibase.com/

Budibase AI: https://docs.budibase.com/docs/quickstart-budibase-ai

4. Directus

Official website: https://directus.io/

GitHub: https://github.com/directus/directus

GitHub Star: 35.9k

Introduction

Directus is a real-time API and app backend for managing SQL database content. It can generate REST / GraphQL APIs and an admin interface on top of existing databases. It supports PostgreSQL, MySQL, SQLite, OracleDB, MariaDB, MS SQL, and other databases, as well as local deployment, private deployment, and cloud services.

In terms of AI capabilities, Directus provides Directus MCP, which allows AI tools such as Claude and ChatGPT to read, create, and manage Directus data. Directus MCP follows the existing permission system, so AI access and modification actions need to go through the same authentication and authorization layer.

What can it do with Hermes?

Directus is more focused on data backends and API management. When Hermes is used with Directus, the focus is not generating pages, but helping teams understand data structures, query business data, and capture common data management actions.

Explain data structures

For existing databases, business users often do not understand how fields relate to each other. Hermes can help organize collections, fields, relationships, and permission boundaries, making the data structure easier to understand.

Assist with data queries and organization

For example, when querying suppliers, contracts, payments, content status, customer records, and similar information, Hermes can turn natural language requirements into more specific data query logic.

Capture data management actions

Actions such as content review, supplier profile maintenance, customer data organization, and contract status checks often repeat. Hermes can organize these data operation processes into Skills, so they can be executed by the same rules later.

Task instruction example

Help me organize the supplier data structure in Directus.

It needs to distinguish:
Supplier basic information.
Contacts.
Contract records.
Payment status.
Cooperation status.
Most recent communication record.

Please explain how these collections should be related and organize a supplier status checking process.

Later, I hope to use natural language to query:
Which supplier contracts are about to expire.
Which suppliers have abnormal payment status.
Which suppliers have not updated communication records for more than 30 days.

Please capture this data organization and query method as a reusable Skill.

Related resources

Documentation: https://directus.io/docs

Directus MCP: https://directus.io/mcp

MCP documentation: https://directus.io/docs/guides/ai/mcp

5. Baserow

Official website: https://baserow.io/

GitHub: https://github.com/baserow/baserow

GitHub Star: 4.9k

Introduction

Baserow is an open source no-code platform that can be used to build databases, applications, automations, and AI Agents. It is often seen as an open source alternative to Airtable. It supports both cloud and self-hosted deployment, and is suitable for managing structured data and lightweight business applications.

Baserow 2.0 introduced Kuma AI assistant, which can create databases, write formulas, and build automations with natural language. It also provides AI fields, an automation builder, workspace search, and other capabilities.

What can it do with Hermes?

Baserow is better suited for building lightweight apps starting from table-based data. When used with Baserow, Hermes can help teams move from “organizing tables” to “capturing data management habits.”

Create table structures and views

For customer lists, supplier lists, content plans, project progress, inventory records, and similar use cases, Hermes can first plan table structures, fields, and views based on business descriptions. Baserow then handles data management.

Organize filters and classification rules

Lightweight apps often rely on different views. Hermes can turn business rules such as “pending review,” “in cooperation,” “about to expire,” and “high priority” into filter conditions and view settings.

Capture lightweight app templates

If a team often uses Baserow to manage similar business data, Hermes can capture field structures, view rules, and status categories as Skills, then reuse them when creating new tables later.

Task instruction example

Help me plan a supplier management table, which will later be created in Baserow.

The fields include:
Supplier name.
Contact person.
Contact information.
Cooperation status.
Contract expiration date.
Payment status.
Owner.
Most recent communication time.
Notes.

Three views need to be created:
Suppliers pending review.
Suppliers in cooperation.
Suppliers with contracts about to expire.

Please design filter conditions for each view and capture this supplier table structure and view rules as a reusable Skill, so it will be easier to create customer tables, channel tables, or partner tables later.

Related resources

Documentation: https://baserow.io/user-docs

Baserow AI: https://baserow.io/product/baserow-ai

FAQ

1. If these platforms already have AI capabilities, why is Hermes still needed?

Built-in AI in these platforms is usually better at completing specific in-product tasks, such as generating pages, SQL, form logic, or component configurations.

The value of Hermes lies in self-hosting, long-term memory, and Skill accumulation. It is better suited for remembering business rules, permission habits, and system configuration methods across tasks and conversations.

2. Which internal tool platforms work best with Hermes?

Platforms that are better suited for Hermes are long-running business system platforms that require continuous maintenance, such as NocoBase, Budibase, Appsmith, Directus, and Baserow.

Among them, NocoBase is better suited for maintaining complete business systems. Appsmith is better suited for internal interfaces and data panels. Budibase is better suited for forms and workflows. Directus and Baserow are better suited for data management scenarios.

3. What kind of teams is Hermes Agent suitable for?

Hermes is better suited for teams that already use self-hosted tools, value data security, need to maintain business systems over the long term, and want AI to remember configuration habits and capture operational experience.

4. Why are self-hosted AI Agents important for enterprise internal tools?

Because internal tools usually contain sensitive business data, such as customers, orders, contracts, approvals, employees, and finance.

When an AI Agent needs to access this data and participate in system operations, teams will pay more attention to where data is stored, how permissions are controlled, how operations are reviewed, and how long-term memory is managed. Self-hosted Agents are better suited for teams that require stronger control.

There are many AI Agent products, but if your team is already using open source internal tool platforms and wants to bring AI Agents into enterprise internal systems in a safer and more controllable way, Hermes Agent is worth trying. If this article is helpful, feel free to share it with friends who are following self-hosted AI Agents and internal tool building.

Related reading

Weekly Updates: Open Source Backup Manager Plugin

NocoBase — Thu, 28 May 2026 10:51:57 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260528

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated with three branches: main , next and develop.

main：The most stable version to date, recommended for installation;
next：Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It's mainly for test users to collect feedback and optimize functions further. Ideal for test users who want to experience new features early and give feedback;
develop：Alpha version, contains the latest feature code, may be incomplete or unstable, mainly for internal dev and rapid iteration. Suited for tech users interested in product's cutting-edge, but with potential issues and incomplete functions. Not for production use.

main

v2.0.58

Release date: 2026-05-28

🎉 New Features

[Workflow] Added an administrator API to rerun started workflow executions from the head node or a specified node. (#9569) by @mytharcher

🚀 Improvements

[client] Removed the Hidden option from menu item settings. (#9595) by @zhangzhonghe

🐛 Bug Fixes

[client]
- Fixed the issue where the v2 mobile date picker popup used the current time instead of the form value. (#9582) by @katherinehhh
- Fixed the issue where time field format settings did not take effect in v2. (#9579) by @katherinehhh
- Increased the file upload limit for the v1 scan input component to 10 MB. (#9580) by @katherinehhh
- Fixed the issue where the hidden state of subform linkage was not synchronized. (#9594) by @katherinehhh
- Fixed the issue where a subtable in a subform could not add a second row. (#9586) by @katherinehhh
- Fixed the issue where page tabs disappeared after switching menus. (#9583) by @zhangzhonghe
[flow-engine] Fixed the issue where table action linkage rules executed incorrectly after a form was successfully submitted in a popup. (#9445) by @gchust
[Workflow: Custom action event] Fixed the issue where custom action table buttons with multiple record contexts incorrectly allowed custom context workflows to be selected. (#9608) by @mytharcher
[File manager]
- Fixed Unicode filename normalization during file uploads to avoid generating object keys with control characters. (#9584) by @mytharcher
- Improved PDF preview failure messages and documented CORS requirements for external storage. (#9600) by @mytharcher Reference: File Preview

v2.0.57

Release date: 2026-05-26

🐛 Bug Fixes

[build] Fixed plugin server obfuscation output to avoid browser globals in Node.js runtime bundles. (#9559) by @Molunerfinn
[Workflow: Manual node] Fixed the issue where temporary saves for manual workflow tasks did not persist submitted form values. (#9554) by @mytharcher
[AI employees] Fixed the incorrect tool name description in the work context prompt. (#9567) by @cgyrock
[File manager] Safely rendered PDF previews with PDF.js instead of iframe-based raw PDF rendering. (#9566) by @mytharcher
[Auth: OIDC] Fixed token leakage when SSO login callbacks received an external redirect URL. by @2013xile
[Workflow: Approval]
- Fixed the issue where the jobs:resume API was not supported by approval nodes. by @mytharcher
- Fixed approval withdrawal to update submitted business data while respecting source collection update permissions. by @mytharcher
- Fixed stale approval todos when approval workflows were terminated by non-approval node failures. by @mytharcher

v2.0.56

Release date: 2026-05-22

🎉 New Features

[Backup manager] Open-sourced the Backup manager plugin. (#9550) by @chenos

🚀 Improvements

[client] Optimized action button display settings. (#9510) by @katherinehhh
[flow-engine] Added search support to v2 field configuration menus. (#9489) by @zhangzhonghe
[Security] Added dependency security review for pull requests. (#9523) by @zhangzhonghe
[Notification manager] Changed the queue strategy to optimize sending performance. (#9407) by @mytharcher
[AI: Knowledge base] Enabled vector storage modification for AI knowledge bases. by @cgyrock
[Workflow: Approval] Improved related approvals with timeline cards. by @zhangzhonghe

🐛 Bug Fixes

[client]
- Fixed the issue where selected values were cleared when dependent association fields changed in data scope linkage. (#9551) by @katherinehhh
- Fixed the issue where a menu badge still displayed a dot when its value was 0. (#9491) by @zhangzhonghe
- Fixed the issue where filter forms could not use current form variables. (#9474) by @zhangzhonghe
- Fixed the issue where narrowed v2 blocks became full width after leaving edit mode. (#9529) by @zhangzhonghe
- Fixed incorrect JS Field menu state in subforms. (#9507) by @gchust
[flow-engine] Fixed the multiple selection issue for external data source fields in v2 forms. (#9542) by @katherinehhh
[AI employees] Fixed an error that occurred when AI employees accessed read-only knowledge bases. (#9539) by @cgyrock
[Calendar] Fixed the issue where more items in the calendar could not be fully displayed. (#9492) by @zhangzhonghe
[Action: Batch update] Fixed the issue where the bulk update action reset the loading state after an update failure. (#9509) by @katherinehhh
[API documentation] Fixed collection API documentation so that query parameters no longer interfere with each other. (#9442) by @jiannx
[Workflow] Added a loading state for manual workflow execution. (#9533) by @mytharcher
[Migration manager] Fixed migration file creation failures when using OceanBase. by @2013xile
[File storage: S3(Pro)] Fixed S3 Pro endpoint handling so server uploads and URL previews do not duplicate the bucket host. by @mytharcher
[Workflow: Approval] Fixed duplicate approval record indexes when delegates occurred concurrently on the same approval job. by @mytharcher

v2.1.0-beta.37

Release date: 2026-05-26

🎉 New Features

[client-v2] Added a Security menu and the Token policy settings page to the v2 admin. The user center now supports Change password. (#9556) by @Molunerfinn
[cli] Added support for basic authentication. (#9558) by @chenos
[Password policy] Migrated the Password policy plugin to the client-v2 admin shell, including the Password policy and Locked users settings pages, and added client-side rule enforcement on the user center Change password form. by @Molunerfinn

🚀 Improvements

[Data visualization] Added client-v2 support for chart blocks. (#9517) by @jiannx
[Workflow] Refactored workflow async-node availability checks. (#9532) by @mytharcher

🐛 Bug Fixes

[build]
- Text assets in server builds are now copied as files instead of being converted into JavaScript modules. (#9565) by @Molunerfinn
- Fixed plugin server obfuscation output to avoid browser globals in Node.js runtime bundles. (#9559) by @Molunerfinn
[client-v2] Fixed browser language metadata so the app page follows the selected application language instead of being marked as English. (#9564) by @Molunerfinn
[File manager] Safely rendered PDF previews with PDF.js instead of iframe-based raw PDF rendering. (#9566) by @mytharcher
[AI employees] Fixed the incorrect tool name description in the work context prompt. (#9567) by @cgyrock
[Workflow: Manual node] Fixed the issue where temporary saves for manual workflow tasks did not persist submitted form values. (#9554) by @mytharcher
[Auth: OIDC] Fixed token leakage when SSO login callbacks received an external redirect URL. by @2013xile
[Workflow: Approval]
- Fixed approval withdrawal to update submitted business data while respecting source collection update permissions. by @mytharcher
- Fixed the issue where the jobs:resume API was not supported by approval nodes. by @mytharcher
- Fixed duplicate approval record indexes when delegates occurred concurrently on the same approval job. by @mytharcher
- Fixed stale approval todos when approval workflows were terminated by non-approval node failures. by @mytharcher

v2.1.0-beta.36

Release date: 2026-05-22

🎉 New Features

[cli] Added backup creation and restore commands. (#9541) by @chenos
[Backup manager] Open-sourced the Backup manager plugin. (#9550) by @chenos
[Theme editor] Added Theme editor support to the v2 interface. (#9530) by @zhangzhonghe
[Two-factor authentication (2FA)] Added support for binding, verification, and configuration of TOTP and two-factor authentication from the v2 client. by @Molunerfinn

🚀 Improvements

[client] Optimized action button display settings. (#9510) by @katherinehhh
[flow-engine] Added search support to v2 field configuration menus. (#9489) by @zhangzhonghe
[cli] Improved the environment authentication flow. (#9546) by @chenos
[Security] Added dependency security review for pull requests. (#9523) by @zhangzhonghe
[Verification] Added v2 client support to the Verification plugin, including the admin settings page, user center entry, and SMS OTP forms. (#9515) by @Molunerfinn
[Authentication] Fixed custom brand settings in the v2 client. (#9543) by @zhangzhonghe
[Block: Map] Added v2 client support for the map plugin. (#9511) by @jiannx
[Custom brand] Added custom brand settings support to the v2 client. by @zhangzhonghe
[AI: Knowledge base] Enabled vector storage modification for AI knowledge bases. by @cgyrock
[Workflow: Approval] Added the async flag for approval instructions to support the new node creation API in the workflow canvas. by @mytharcher

🐛 Bug Fixes

[client]
- Fixed the issue where selected values were cleared when dependent association fields changed in data scope linkage. (#9551) by @katherinehhh
- Fixed dev mode loading for built storage plugins that depend on named exports from local source plugins. (#9548) by @Molunerfinn
- Fixed incorrect JS Field menu state in subforms. (#9507) by @gchust
- Fixed the issue where narrowed v2 blocks became full width after leaving edit mode. (#9529) by @zhangzhonghe
[client-v2] Fixed inconsistent dnd-kit dependency registration. (#9544) by @jiannx
[flow-engine] Fixed the multiple selection issue for external data source fields in v2 forms. (#9542) by @katherinehhh
[Block: iframe] Fixed the issue where iframe content did not fill the configured block height. (#9540) by @katherinehhh
[AI employees]
- Fixed an error that occurred when AI employees accessed read-only knowledge bases. (#9539) by @cgyrock
- Fixed the issue where AI tool call cards did not appear immediately when streamed tool events were split. (#9534) by @2013xile
- Fixed an error that occurred when AI employees accessed read-only knowledge bases. (#9538) by @cgyrock
[Action: Export records] Improved field configuration performance when there are many association fields. (#9524) by @katherinehhh
[Action: Batch update] Fixed the issue where the bulk update action reset the loading state after an update failure. (#9509) by @katherinehhh
[Workflow] Added a loading state for manual workflow execution. (#9533) by @mytharcher
[Localization] Fixed built-in localization reference translations for AI translation tasks. (#9531) by @2013xile
[Migration manager] Fixed migration file creation failures when using OceanBase. by @2013xile
[File storage: S3(Pro)] Fixed S3 Pro endpoint handling so server uploads and URL previews do not duplicate the bucket host. by @mytharcher

develop

v2.1.0-alpha.40

Release date: 2026-05-22

🎉 New Features

[cli] Added backup creation and restore commands. (#9541) by @chenos
[Backup manager] Open-sourced the Backup manager plugin. (#9550) by @chenos
[Theme editor] Added Theme editor support to the v2 interface. (#9530) by @zhangzhonghe
[Two-factor authentication (2FA)] Added support for binding, verification, and configuration of TOTP and two-factor authentication from the v2 client. by @Molunerfinn

🚀 Improvements

[cli] Improved the environment authentication flow. (#9546) by @chenos
[flow-engine] Added search support to v2 field configuration menus. (#9489) by @zhangzhonghe
[client] Optimized action button display settings. (#9510) by @katherinehhh
[Security] Added dependency security review for pull requests. (#9523) by @zhangzhonghe
[Verification] Added v2 client support to the Verification plugin, including the admin settings page, user center entry, and SMS OTP forms. (#9515) by @Molunerfinn
[Authentication] Fixed custom brand settings in the v2 client. (#9543) by @zhangzhonghe
[Block: Map] Added v2 client support for the map plugin. (#9511) by @jiannx
[Custom brand] Added custom brand settings support to the v2 client. by @zhangzhonghe
[AI: Knowledge base] Enabled vector storage modification for AI knowledge bases. by @cgyrock
[Workflow: Approval] Added the async flag for approval instructions to support the new node creation API in the workflow canvas. by @mytharcher

🐛 Bug Fixes

[client]
- Fixed dev mode loading for built storage plugins that depend on named exports from local source plugins. (#9548) by @Molunerfinn
- Fixed the issue where narrowed v2 blocks became full width after leaving edit mode. (#9529) by @zhangzhonghe
- Fixed the issue where selected values were cleared when dependent association fields changed in data scope linkage. (#9551) by @katherinehhh
- Fixed incorrect JS Field menu state in subforms. (#9507) by @gchust
[client-v2] Fixed inconsistent dnd-kit dependency registration. (#9544) by @jiannx
[flow-engine] Fixed the multiple selection issue for external data source fields in v2 forms. (#9542) by @katherinehhh
[Block: iframe] Fixed the issue where iframe content did not fill the configured block height. (#9540) by @katherinehhh
[Action: Export records] Improved field configuration performance when there are many association fields. (#9524) by @katherinehhh
[AI employees]
- Fixed an error that occurred when AI employees accessed read-only knowledge bases. (#9539) by @cgyrock
- Fixed an error that occurred when AI employees accessed read-only knowledge bases. (#9538) by @cgyrock
- Fixed the issue where AI tool call cards did not appear immediately when streamed tool events were split. (#9534) by @2013xile
[Localization] Fixed built-in localization reference translations for AI translation tasks. (#9531) by @2013xile
[Action: Batch update] Fixed the issue where the bulk update action reset the loading state after an update failure. (#9509) by @katherinehhh
[Workflow] Added a loading state for manual workflow execution. (#9533) by @mytharcher
[Migration manager] Fixed migration file creation failures when using OceanBase. by @2013xile
[File storage: S3(Pro)] Fixed S3 Pro endpoint handling so server uploads and URL previews do not duplicate the bucket host. by @mytharcher
[Workflow: Approval] Fixed duplicate approval record indexes when delegates occurred concurrently on the same approval job. by @mytharcher

OpenClaw and 5 Open-Source Tools for Monitoring Business Workflows

NocoBase — Wed, 27 May 2026 09:47:50 +0000

Originally published at https://www.nocobase.com/en/blog/openclaw-open-source-enterprise-tools

OpenClaw first gained attention because it directly responded to what people expected from AI: the ability to take action.

We previously wrote an article introducing a group of open source AI Agent projects similar to OpenClaw. The trend was clear at the time: AI Agents were moving beyond chat windows into real workflows, where they could handle more concrete tasks.

Recently, however, OpenClaw no longer seems to be as popular as it was at the beginning.

Compared with Agent tools focused more on code generation, workflow orchestration, or enterprise AI applications, OpenClaw seems to have gradually faded from the center of the conversation.

Is anyone still using OpenClaw? What are they actually using it for?

In the Reddit community, people shared how they use OpenClaw in daily work. From the discussion, AI and news tracking, reminders and follow-ups, regular summaries, backend monitoring, task organization, and note organization are all common use cases. Some comments also mentioned more business-oriented scenarios, such as financial reminders, customer support triage, marketing assistants, and using Telegram to connect ERP, CRM, and automation tools to generate daily briefings and end-of-day summaries.

In fact, the value of OpenClaw is not limited to controlling a computer through chat software. It can also continuously monitor regular, recurring, and easily overlooked business changes.

Next, we will introduce several types of open source tools that work well with OpenClaw and explore how it can better enter enterprise internal workflows.

1. NocoBase

Official website:https://www.nocobase.com/

GitHub:https://github.com/nocobase/nocobase

GitHub Star: 22.5k

Introduction

NocoBase is an open source AI no-code / low-code platform that is well suited for building enterprise internal systems and business workspaces. It can be used not only to build individual business systems such as CRM, ERP, and project management systems, but also to support more complex enterprise internal applications.

It supports multiple types of data sources and uses data models to organize complex business relationships. Its permission control can go down to the field level. Workflows, audit logs, plugins, and other capabilities help teams manage business data, process rules, operation records, and system extensions in one platform.

In terms of AI capabilities, NocoBase is not just about generating a one-time app. AI can take part in both system building and daily business operations. NocoBase supports AI Employees, AI Skills, CLI, and other capabilities that can help with data model design, page configuration, workflow orchestration, permission setup, and plugin management. AI Employees can also participate in data analysis, risk monitoring, approval collaboration, and task distribution, allowing AI to work inside existing business systems.

Suitable scenarios

Enterprise internal business systems: Build internal applications such as CRM, ERP, project management, asset management, approval, and ticketing systems, while managing data, permissions, and workflows in one place.
Cross-department collaboration workflows: Record tasks, approvals, risks, feedback, owners, and processing status, so different roles can collaborate around the same set of business data.
AI-assisted business workspace: Support business scenarios where AI and humans work together, such as customer feedback, exception records, task assignment, and data analysis. After connecting OpenClaw to common chat tools such as Feishu, Telegram, and WhatsApp, teams can directly start queries, receive reminders, and trigger tasks from chat interfaces, then organize the results into Feishu Docs, Google Sheets, or other collaboration tools.

For example, in a CRM scenario, you can send OpenClaw an instruction directly in Telegram: check the customer leads in NocoBase, filter out customers with a total spend above 30,000, and organize them into a follow-up list. After receiving the task, OpenClaw can call customer data from NocoBase, extract company names, total spend, membership level, contacts, regions, and other information, then generate a Google Sheet so the team can review the list, prioritize high-value customers, and assign next steps.

Task instruction example:

Help me check the customer leads in NocoBase. Filter out customers with a total spend above 30,000, organize them into today’s priority follow-up list, and generate it as a Google Sheet.

Please include company name, total spend, membership level, contact person, and region in the list. Also briefly mark which customers should be followed up first.

Related resources

Documentation: https://docs.nocobase.com/

AI documentation: https://docs.nocobase.com/en/ai/

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

OpenClaw + NocoBase: https://docs.nocobase.com/en/ai/openclaw

2. n8n

Official website:https://n8n.io/

GitHub:https://github.com/n8n-io/n8n

GitHub Star: 190k

Introduction

n8n is a workflow automation platform for technical teams. It supports visual workflow building, custom code, self-hosted deployment, and 400+ integrations. It is suitable for connecting different systems, APIs, databases, and business tools, turning repetitive business processes into automated workflows that can run continuously.

n8n supports large language models, AI Agents, tool calling, and private data inside workflows. Teams can use it to build AI automation workflows for email summaries, lead processing, content generation, customer support triage, data queries, and more. They can also view and control Agent execution steps on the workflow canvas.

Suitable scenarios

Cross-system data synchronization: Connect CRM, forms, databases, email, Feishu, Slack, and other tools to reduce manual copying and repeated data entry.
Business process automation: Handle fixed processes such as form submissions, lead assignment, ticket routing, approval reminders, and status synchronization.
AI workflow orchestration: Combine model calls, data reading, content generation, summary organization, and result writing into stable workflows.

For example, when processes such as sales leads, customer feedback, form submissions, and ticket assignment are already running automatically in n8n, OpenClaw can check every day whether any process failed, whether any data failed to move to the next step, or whether a notification was sent but never followed up.

Task instruction example:

Every morning at 10, check the n8n workflow execution records related to sales leads, customer feedback, and project notifications.

Please find workflows from the past 24 hours that failed, still failed after retries, or triggered notifications but had no follow-up processing records, and organize them into today’s workflow issue report.

Related resources

Documentation: https://docs.n8n.io/

AI documentation: https://docs.n8n.io/advanced-ai/

AI workflow introduction: https://docs.n8n.io/advanced-ai/intro-tutorial/

AI Workflow Builder: https://docs.n8n.io/advanced-ai/ai-workflow-builder/

3. RAGFlow

Official website:https://ragflow.io/

GitHub:https://github.com/infiniflow/ragflow

GitHub Star: 81.2k

Introduction

RAGFlow is an open source RAG engine for handling enterprise internal documents, knowledge bases, customer feedback, ticket records, product materials, and project materials. It can turn scattered materials into searchable, answerable, and citable knowledge sources, giving large language models a more reliable context layer.

RAGFlow combines RAG and Agent capabilities. It supports preset Agent templates, memory, data synchronization, document parsing, and knowledge retrieval. It also provides a Skill for OpenClaw, which can be used to access RAGFlow datasets through OpenClaw.

Suitable scenarios

Customer feedback knowledge base: Accumulate customer issues, ticket records, solutions, and frequent requests.
Internal document Q&A: Query product documents, operation manuals, policy documents, SOPs, and project materials.
Knowledge base gap identification: Find questions that users repeatedly ask but that are not covered in the documentation, then help drive FAQ or SOP updates.

For example, when a certain type of issue appears repeatedly in customer feedback and tickets, but the knowledge base or FAQ does not provide a clear answer, OpenClaw can organize a knowledge base optimization report and remind the documentation, support, or product team to add the missing content.

Task instruction example:

Every Friday at 3 PM, check customer feedback, ticket records, and product documents in RAGFlow.

Please find questions that users repeatedly ask but that have no clear answer in the knowledge base, and organize this week’s knowledge base gap report, including suggested FAQ titles, reference sources, and responsible teams.

Related resources

Documentation: https://ragflow.io/docs/

API documentation: https://ragflow.io/docs/dev/http_api_reference

RAGFlow + OpenClaw: https://ragflow.io/blog/ragflow-x-openclaw-the-enterprise-aware-claw

RAGFlow Skill: https://clawskills.sh/skills/angusthefuzz-ragflow

4. ERPNext

Official website:https://frappe.io/erpnext

GitHub:https://github.com/frappe/erpnext

GitHub Star: 35k

Introduction

ERPNext is an open source ERP system that covers enterprise operations modules such as accounting, procurement, sales, CRM, inventory, manufacturing, projects, POS, quality, and support. It is suitable for recording data from daily business operations, including orders, inventory, procurement, suppliers, customers, invoices, manufacturing work orders, and project costs.

ERPNext is more of a standard ERP system and does not position native AI Agent capabilities as its core selling point. Its value lies in providing structured and traceable business data, making it a suitable data source for AI analysis, anomaly detection, report generation, and business Q&A.

Suitable scenarios

Inventory and procurement management: Manage materials, inventory, purchase orders, supplier delivery, and inventory alerts.
Sales order management: Track customer orders, delivery status, sales invoices, and order fulfillment.
Manufacturing and project cost management: Record manufacturing work orders, production progress, project costs, and resource consumption.

For example, OpenClaw can regularly check whether inventory has fallen below the safety stock level, purchase orders have passed their expected arrival dates, sales orders have missed promised shipping dates, key customer orders have abnormal status, or return rates have suddenly increased.

Task instruction example:

Every morning at 10, check inventory, procurement, and sales order data in ERPNext.

Please filter records where inventory is below safety stock, purchases are overdue and not delivered, sales orders are overdue and not shipped, or key customer orders are abnormal, and generate today’s supply chain exception report.

Related resources

Documentation: https://docs.erpnext.com/homepage

Frappe Framework: https://github.com/frappe/frappe

Frappe REST API documentation: https://docs.frappe.io/framework/user/en/api/rest

Frappe JS SDK: https://github.com/frappe/frappe-js-sdk

5. Plane

Official website:https://plane.so/

GitHub:https://github.com/makeplane/plane

GitHub Star: 49.7k

Introduction

Plane is an open source project management platform that can be used as an alternative to Jira, Linear, Monday, and ClickUp. It helps teams manage tasks, cycles, project documents, product roadmaps, and team collaboration. It is suitable for product, development, design, operations, and other teams to track requirements, bugs, tasks, milestones, and project progress.

Plane brings projects, documents, and AI workflows into the same workspace. Plane AI can answer questions based on context from projects, cycles, and pages. It can also generate work structures from prompts, helping teams with task triage, progress summaries, and project collaboration.

Suitable scenarios

R&D task management: Track requirements, bugs, tasks, cycles, and release progress.
Product roadmap management: Manage product plans, priorities, milestones, and cross-team collaboration items.
Project risk checks: Identify delayed tasks, blockers, unassigned tasks, and requirements that have not been updated for a long time.

For example, project managers do not need to check every task manually every day. Instead, they can ask OpenClaw to summarize project risks that need attention every afternoon and push them to the responsible owners.

Task instruction example:

Every afternoon at 4, check the issues and cycles of this week’s active projects in Plane.

Please find tasks that are close to the deadline but have no updates, have been blocked for more than 48 hours, have no owner, or have been waiting for review for more than 24 hours, and organize them into today’s project blocker summary.

Related resources

Documentation: https://docs.plane.so/

Developer documentation: https://developers.plane.so/

API documentation: https://developers.plane.so/api-reference/introduction

FAQ

1. What kind of work is suitable for OpenClaw?

Work suitable for OpenClaw usually has three characteristics: a fixed checking frequency, a clear data source, and relatively clear judgment rules.

For example, checking every day whether CRM leads are overdue for follow-up, ERP inventory is below safety stock, project tasks are delayed, tickets are piling up, the knowledge base lacks answers to frequent questions, or automation workflows have failed. These tasks do not necessarily require AI to make final decisions directly, but they are well suited for OpenClaw to first detect issues, generate summaries, and push them to the responsible person for handling.

2. Is OpenClaw suitable for enterprise internal systems?

In enterprise internal systems, OpenClaw can regularly check data changes across CRM, ERP, project management, knowledge bases, and workflow automation tools, then organize exceptions, delays, opportunities, and pending items. This reduces the time spent manually checking multiple systems and helps teams identify business risks earlier.

3. If an enterprise has many business systems, what tool should be used to integrate them?

If an enterprise already has many business systems, such as CRM, ERP, project management, knowledge bases, forms, ticketing systems, and data dashboards, it can consider using NocoBase to build a unified business workspace.

NocoBase can organize leads, tasks, feedback, exceptions, approvals, and knowledge base optimization tasks from different systems into structured data, then manage them through pages, permissions, workflows, and plugins. OpenClaw can regularly check this data and push out items that need attention. NocoBase then supports the follow-up process, including viewing, assignment, follow-up, and review.

4. What should enterprises pay attention to when using OpenClaw with open source tools?

They should pay close attention to permissions, data security, logging, and human confirmation mechanisms.

OpenClaw may access business systems, call tools, read data, or trigger automation workflows. Therefore, it is recommended to start with low-risk tasks such as status checks, summary generation, reminder pushes, and exception recording. For high-risk actions involving financial approvals, customer commitments, contract confirmation, personnel handling, and similar matters, a human confirmation step should be retained.

5. Which enterprise scenario is best for trying OpenClaw first?

It is recommended to start with scenarios that are low risk, high frequency, and rule based.

Examples include sales lead follow-up reminders, project delay checks, knowledge base gap reports, automation workflow failure monitoring, inventory alert summaries, and ticket backlog reminders. These tasks do not require OpenClaw to make key decisions directly, but they can significantly reduce manual inspection costs and make the results easier to validate.

6. What should enterprises pay attention to when using OpenClaw with open source tools?

When enterprises use OpenClaw, they should pay close attention to permissions, data security, logging, and human confirmation mechanisms.

OpenClaw may access business systems, read data, call tools, or trigger automation workflows. Therefore, it is recommended to start with low-risk tasks such as status checks, summary generation, reminder pushes, and exception recording. For high-risk actions involving financial approvals, customer commitments, contract confirmation, personnel handling, and similar matters, a human confirmation step should be retained.

It can also be combined with internal tool platforms such as NocoBase. NocoBase supports role permissions, data table permissions, operation permissions, workflows, audit logs, and other capabilities. It can help teams control what different roles can see, what they can operate, and whether key processes require human approval. OpenClaw handles detection and reminders, while the business system handles permission control, process records, and follow-up actions.

Conclusion

OpenClaw is only a starting point. In future enterprise applications, Agents will no longer be just assistants inside chat interfaces, nor temporary executors that call tools when needed. They will gradually become an intelligent collaboration layer within enterprise internal tool systems.

People will no longer need to enter every system frequently to check status, find issues, and follow up on progress. Agents can continuously monitor business changes and bring the items that require judgment and action back to people.

If you find this article helpful, feel free to share it with friends who are exploring AI Agents and enterprise internal tools.

Related reading

Weekly Updates: Added client-v2 support for the Kanban plugin

NocoBase — Thu, 21 May 2026 13:09:32 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260521

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated with three branches: main , next and develop.

main：The most stable version to date, recommended for installation;
next：Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It's mainly for test users to collect feedback and optimize functions further. Ideal for test users who want to experience new features early and give feedback;
develop：Alpha version, contains the latest feature code, may be incomplete or unstable, mainly for internal dev and rapid iteration. Suited for tech users interested in product's cutting-edge, but with potential issues and incomplete functions. Not for production use.

main

v2.0.55

Release date: 2026-05-18

🚀 Improvements

[AI employees] Prompt on duplicate table name when saving to vector database (#9497) by cgyrock
[AI: Knowledge base] Prompt on duplicate table name when saving to vector database by cgyrock

🐛 Bug Fixes

[client]
- Fixed an issue where current popup record variables could not be resolved in action button event flows. (#9495) by gchust
- Fixed an issue where JS field values in subforms were not correctly set during form submission. (#9496) by gchust
[File manager] Fix file manager tx-cos uploads missing file size metadata. (#9499) by mytharcher
[Data source: Main] Fix the issue where field options are written into the schema after syncing fields (#9505) by 2013xile
[WEB client] Clean blocks data after remove menus. (#9459) by gchust
[AI employees] Fix AI employee OSS file read errors (#9493) by cgyrock
[Action: Import records] Fix the issue where imported record on date-like fields shows wrong date (#9463) by mytharcher
[Action: Export records Pro] Fix the issue where error thrown when export attachment from attachment url field by mytharcher
[Action: Import records Pro] fix timezone handling for pro xlsx imports by mytharcher

v2.0.53

Release date: 2026-05-14

🚀 Improvements

[flow-engine] Added an unsaved changes confirm message when closing the event flow configuration page with unsaved data present. (#9449) by gchust

🐛 Bug Fixes

[client]
- fix prevent opening quick edit for association fields in table (#9469) by katherinehhh
- Fixed display-only relation fields in sub-tables not showing or not clickable after refresh. (#9453) by jiannx
- fix multiple select fields in v2 data blocks should display option labels instead of values (#9472) by katherinehhh
[Block: Multi-step form] fix scrollbar issue when enabling full-height in v1 step form block (#9468) by katherinehhh

v2.1.0-beta.35

Release date: 2026-05-20

🚀 Improvements

[client] Share condition evaluation between v1 and v2 apps (#9522) by zhangzhonghe
[Localization] Improved Lina localization translation tasks with translation scope, reference language settings, and quick editing (#9521) by 2013xile
[Workflow: Approval] Improve related approvals with timeline cards by zhangzhonghe

🐛 Bug Fixes

[undefined] align nginx config paths (#9528) by chenos
[cli-v1] Fixed create-nocobase-app development startup by reusing packaged app shells while enabling local plugin development. (#9471) by Molunerfinn
[client]
- Fix the issue where a menu badge still shows a dot when its value is 0 (#9491) by zhangzhonghe
- Fix the issue where filter forms cannot use current form variables (#9474) by zhangzhonghe
[Authentication] Prevent the server from crashing when a WebSocket auth token references an authenticator whose auth type plugin is unloaded or missing. (#9514) by Molunerfinn
[Calendar]
- Fix the issue where calendar more items cannot be fully displayed (#9492) by zhangzhonghe
- Fixed the cursor style for event items in the calendar more-events overlay (#9519) by jiannx
[License settings] resolve symlinked bundled deps (#9518) by chenos

v2.1.0-beta.34

Release date: 2026-05-19

🎉 New Features

[Block: Kanban] Added client-v2 support for the Kanban plugin (#9475) by jiannx

🚀 Improvements

[cli] Improved the NocoBase CLI prompt experience by migrating setup and management workflows to Inquirer, and fixed related install, skills, and Docker runtime issues. (#9452) by chenos
[AI employees] Prompt on duplicate table name when saving to vector database (#9497) by cgyrock
[Notification manager] Change queue strategy to optimize sending performance (#9407) by mytharcher
[Workflow: Custom action event] Migrated the block-workbench and workflow-custom-action-trigger plugins to client v2, including their action models and QR scanner flow. (#9494) by jiannx
[Authentication] Implement the Authenticators settings page in client-v2 and ship reusable client-v2 table, variable input, and form primitives. (#9457) by Molunerfinn
[AI: Knowledge base] Prompt on duplicate table name when saving to vector database by cgyrock
[Auth: SAML 2.0] Add client-v2 entries for the CAS and SAML authentication plugins so they work with the v2 sign-in page and Authenticators settings. by Molunerfinn

🐛 Bug Fixes

[client-v2]
- Fixed the Kanban plugin v2 route failing to load because dnd-kit dependencies were not provided by the client. (#9516) by jiannx
- The shared v2 Table component now shows the page-size selector by default, matching v1 behavior. (#9512) by Molunerfinn
[client]
- Fixed an issue where JS field values in subforms were not correctly set during form submission. (#9496) by gchust
- Fixed an issue where current popup record variables could not be resolved in action button event flows. (#9495) by gchust
[flow-engine] Fixed incorrect error message in browser's console. (#9502) by gchust
[AI employees]
- Fix issue where operator role permissions are not taking effect in AI employee nodes (#9513) by cgyrock
- Fix AI employee OSS file read errors (#9493) by cgyrock
[API documentation] Fixed collection API documentation so query parameters no longer interfere with each other (#9442) by jiannx
[Data source: Main] Fix the issue where field options are written into the schema after syncing fields (#9505) by 2013xile
[Workflow: JavaScript] Fixed workflow JavaScript QuickJS runtime package loading in production builds. (#9503) by mytharcher
[WEB client] Clean blocks data after remove menus. (#9459) by gchust
[Action: Import records] Fix the issue where imported record on date-like fields shows wrong date (#9463) by mytharcher
[Action: Import records Pro] fix timezone handling for pro xlsx imports by mytharcher
[Auth: SAML 2.0] Fix SAML auto-redirect interceptor flickering the app shell and double-opening drawers on every navigation. by Molunerfinn
[Action: Export records Pro] Fix the issue where error thrown when export attachment from attachment url field by mytharcher

v2.1.0-beta.33

Release date: 2026-05-15

🎉 New Features

[Block: Markdown] Added client v2 support for Markdown blocks (#9487) by jiannx
[Block: List] List blocks support client-v2 (#9486) by jiannx
[Calendar] Added client v2 support for the Calendar plugin. (#9464) by jiannx
[Block: Tree] Added client-v2 support for the tree filter block. (#9466) by jiannx

🚀 Improvements

[flow-engine] Added an unsaved changes confirm message when closing the event flow configuration page with unsaved data present. (#9449) by gchust
[Data source manager] Optimize the data modeling API to support creating comment collections with AI, configuring relationship fields for external data sources, and setting field validation rules (#9480) by 2013xile
[Block: GridCard] Updated grid card plugin to support client v2 (#9484) by jiannx
[Block: iframe] Added v2 support for the iframe block. (#9485) by jiannx
[AI employees] AI employee parallel conversation Interaction and performance optimization (#9462) by cgyrock

🐛 Bug Fixes

[client]
- Added the "After successful submission" setting for form submit actions. (#9414) by jiannx
- fix prevent opening quick edit for association fields in table (#9469) by katherinehhh
- Fixed display-only relation fields in sub-tables not showing or not clickable after refresh. (#9453) by jiannx
- Fixed the issue where legacy default value settings can't be removed. (#9470) by gchust
- fix multiple select fields in v2 data blocks should display option labels instead of values (#9472) by katherinehhh
[client-v2]
- Fix issue where the title field option list is empty for relation fields in table blocks (#9490) by katherinehhh
- Keep empty groups after filtering v1 menus in the v2 layout (#9478) by zhangzhonghe
[flow-engine] Fixed unstable relation-field submenus in submodel menus (#9417) by jiannx
[File manager] Fix file manager tx-cos uploads missing file size metadata. (#9499) by mytharcher
[AI employees] Fixed plugin-ai load error (#9483) by cgyrock
[Block: Multi-step form] fix scrollbar issue when enabling full-height in v1 step form block (#9468) by katherinehhh
[Workflow: Webhook] Fix the issue where creating response node intercepted by validation of statusCode configuration by mytharcher
[Collection field: Signature] Resolve signature box display issue on mobile by chenzhizdt

develop

v2.1.0-alpha.39

Release date: 2026-05-20

🎉 New Features

[Block: Kanban] Added client-v2 support for the Kanban plugin (#9475) by jiannx

🚀 Improvements

[client] Share condition evaluation between v1 and v2 apps (#9522) by zhangzhonghe
[Localization] Improved Lina localization translation tasks with translation scope, reference language settings, and quick editing (#9521) by 2013xile
[AI employees] Prompt on duplicate table name when saving to vector database (#9497) by cgyrock
[Notification manager] Change queue strategy to optimize sending performance (#9407) by mytharcher
[Workflow: Custom action event] Migrated the block-workbench and workflow-custom-action-trigger plugins to client v2, including their action models and QR scanner flow. (#9494) by jiannx
[Authentication] Implement the Authenticators settings page in client-v2 and ship reusable client-v2 table, variable input, and form primitives. (#9457) by Molunerfinn
[AI: Knowledge base] Prompt on duplicate table name when saving to vector database by cgyrock
[Auth: SAML 2.0] Add client-v2 entries for the CAS and SAML authentication plugins so they work with the v2 sign-in page and Authenticators settings. by Molunerfinn
[Workflow: Approval] Improve related approvals with timeline cards by zhangzhonghe

🐛 Bug Fixes

[undefined] align nginx config paths (#9528) by chenos
[cli-v1] Fixed create-nocobase-app development startup by reusing packaged app shells while enabling local plugin development. (#9471) by Molunerfinn
[client]
- Fix the issue where filter forms cannot use current form variables (#9474) by zhangzhonghe
- Fix the issue where a menu badge still shows a dot when its value is 0 (#9491) by zhangzhonghe
[client-v2]
- The shared v2 Table component now shows the page-size selector by default, matching v1 behavior. (#9512) by Molunerfinn
- Fixed the Kanban plugin v2 route failing to load because dnd-kit dependencies were not provided by the client. (#9516) by jiannx
[Calendar]
- Fixed the cursor style for event items in the calendar more-events overlay (#9519) by jiannx
- Fix the issue where calendar more items cannot be fully displayed (#9492) by zhangzhonghe
[License settings] resolve symlinked bundled deps (#9518) by chenos
[AI employees]
- Fix issue where operator role permissions are not taking effect in AI employee nodes (#9513) by cgyrock
- Fix AI employee OSS file read errors (#9493) by cgyrock
[Authentication] Prevent the server from crashing when a WebSocket auth token references an authenticator whose auth type plugin is unloaded or missing. (#9514) by Molunerfinn
[API documentation] Fixed collection API documentation so query parameters no longer interfere with each other (#9442) by jiannx
[Data source: Main] Fix the issue where field options are written into the schema after syncing fields (#9505) by 2013xile
[Auth: SAML 2.0] Fix SAML auto-redirect interceptor flickering the app shell and double-opening drawers on every navigation. by Molunerfinn

v2.1.0-alpha.38

Release date: 2026-05-18

🐛 Bug Fixes

[client]
- Fixed an issue where current popup record variables could not be resolved in action button event flows. (#9495) by gchust
- Fixed an issue where JS field values in subforms were not correctly set during form submission. (#9496) by gchust
[flow-engine] Fixed incorrect error message in browser's console. (#9502) by gchust
[Workflow: JavaScript] Fixed workflow JavaScript QuickJS runtime package loading in production builds. (#9503) by mytharcher
[Action: Import records] Fix the issue where imported record on date-like fields shows wrong date (#9463) by mytharcher
[Action: Import records Pro] fix timezone handling for pro xlsx imports by mytharcher
[Action: Export records Pro] Fix the issue where error thrown when export attachment from attachment url field by mytharcher

v2.1.0-alpha.37

Release date: 2026-05-17

🐛 Bug Fixes

[WEB client] Clean blocks data after remove menus. (#9459) by gchust

v2.1.0-alpha.36

Release date: 2026-05-16

🎉 New Features

[Block: Markdown] Added client v2 support for Markdown blocks (#9487) by jiannx
[Block: List] List blocks support client-v2 (#9486) by jiannx

🚀 Improvements

[flow-engine] Added an unsaved changes confirm message when closing the event flow configuration page with unsaved data present. (#9449) by gchust
[cli] Improved the NocoBase CLI prompt experience by migrating setup and management workflows to Inquirer, and fixed related install, skills, and Docker runtime issues. (#9452) by chenos
[Data source manager] Optimize the data modeling API to support creating comment collections with AI, configuring relationship fields for external data sources, and setting field validation rules (#9480) by 2013xile
[Block: GridCard] Updated grid card plugin to support client v2 (#9484) by jiannx
[Block: iframe] Added v2 support for the iframe block. (#9485) by jiannx

🐛 Bug Fixes

[client]
- Fixed display-only relation fields in sub-tables not showing or not clickable after refresh. (#9453) by jiannx
- Added the "After successful submission" setting for form submit actions. (#9414) by jiannx
[client-v2] Fix issue where the title field option list is empty for relation fields in table blocks (#9490) by katherinehhh
[flow-engine] Fixed unstable relation-field submenus in submodel menus (#9417) by jiannx
[File manager] Fix file manager tx-cos uploads missing file size metadata. (#9499) by mytharcher
[Collection field: Signature] Resolve signature box display issue on mobile by chenzhizdt

v2.1.0-alpha.35

Release date: 2026-05-14

🎉 New Features

[undefined] Add a new AI employee, Localization Engineer Lina, to assist with localization translation tasks (#9434) by 2013xile Reference: Localization Management Lina: Localization Engineer Use Lina and local HY-MT1.5-1.8B to translate localization entries
[Calendar] Added client v2 support for the Calendar plugin. (#9464) by jiannx
[Block: Tree] Added client-v2 support for the tree filter block. (#9466) by jiannx
[File storage: S3(Pro)] Support uploading files via S3 Pro storage in the v2 file manager. by Molunerfinn

🚀 Improvements

[build] Added regression coverage to keep deleteServerFiles from removing client and client-v2 build artifacts across Windows and POSIX paths. (#9318) by Molunerfinn
[client] exclude already associated records in association selection dialog of one-to-many table block (#9448) by katherinehhh
[AI employees] AI employee parallel conversation Interaction and performance optimization (#9462) by cgyrock
[File manager] Third-party storage plugins can now register their own storage type form on the v2 file manager settings page. (#9439) by Molunerfinn
[AI: Knowledge base] The unique identifier for a knowledge base is configurable at the time of creation by cgyrock

🐛 Bug Fixes

[client]
- fix prevent opening quick edit for association fields in table (#9469) by katherinehhh
- fix multiple select fields in v2 data blocks should display option labels instead of values (#9472) by katherinehhh
- Fix duplicate table requests when filter forms have default values (#9423) by zhangzhonghe
- Fixed the issue where legacy default value settings can't be removed. (#9470) by gchust
- Fixed the issue where can't select options for association's select field. (#9088) by gchust
- Fix the issue where system settings appear empty after submitting (#9458) by zhangzhonghe
- Fixed an issue where the target block data scope was set incorrectly when deselecting row data in a table block event flow. (#9443) by gchust
- fix error when changing title field of association field in v2 table block (#9451) by katherinehhh
- Fixed V2 linkage rules to support setting selectable options for fields (#9399) by jiannx
[client-v2]
- Keep empty groups after filtering v1 menus in the v2 layout (#9478) by zhangzhonghe
- Fix the issue where the page turns blank behind the plugin enabling dialog (#9455) by zhangzhonghe
- Fix v1 admin pages crashing when they reference v2 plugin modules in production builds. (#9460) by Molunerfinn
[cli-v1] Fixed development startup failures in apps created with create-nocobase-app caused by app-dev client path resolution. (#9465) by Molunerfinn
[server] fix(file-manager): force download active content files in local/public storage (#9437) by mytharcher
[AI employees]
- Fixed plugin-ai load error (#9483) by cgyrock
- Fixed Ollama test flight requiring key input (#9450) by cgyrock
[Block: Multi-step form] fix scrollbar issue when enabling full-height in v1 step form block (#9468) by katherinehhh
[Departments] fix translation conflict between add user and add department buttons in Users & Permissions settings (#9456) by katherinehhh
[Workflow] fix: restore helper text in FlowModel workflow binding dialogs for operation and custom action events (#9447) by mytharcher
[Block: Markdown] Fix the issue of v2 Markdown block reporting errors (#9440) by zhangzhonghe
[Workflow: Webhook] Fix the issue where creating response node intercepted by validation of statusCode configuration by mytharcher
[Workflow: Approval]
- Fix approval form layout on mobile devices by zhangzhonghe
- Fix duplicate approval record index when delegating approval tasks. by mytharcher
[Backup manager] Fixed an issue where backups would fail with an error when files could not be found. by gchust