Best Arcade.dev alternatives for AI agent integrations in 2026

TL;DR

Arcade.dev is an MCP runtime that executes authenticated tool calls for AI agents. It works well for MCP-first teams that need a hosted runtime and user-scoped auth. But production AI agents usually need more than tool calls: continuous data syncs for RAG, webhook ingestion, and deep observability across API integrations.

If you are evaluating alternatives, pick the one that covers your full integration surface: not just the tool calls you need today, but the data syncs, webhooks, auth, and observability your agents will need once they ship to real customers.

Top Arcade.dev alternatives for 2026:

• Nango: Best for teams building production AI agent API integrations that need tool calls, data syncs, webhooks, and auth on a single code-first platform. Supports 700+ APIs with open-source tools and works with Claude Code, Cursor, and other AI coding agents.
• Composio: An MCP-native alternative aimed mainly at internal and personal automation agents. Larger pre-built catalog than Arcade (500+ apps), but closed-source tools and no data syncs, webhooks, or per-customer configuration.
• Pipedream Connect: Fits teams that prefer a low-code, UI-based workflow builder with a large action library.
• Merge Agent Handler: Fits teams that want pre-built MCP tool-packs for common SaaS actions and don't need custom tool logic or data syncs.

Why teams look for Arcade.dev alternatives

Arcade.dev positions itself as the MCP runtime that makes AI agents production-ready. It handles OAuth, runs tool calls, and supports server-level and tool-level authorization.

That positioning works well for a specific profile: teams that are already committed to MCP, want a hosted runtime, and only need tool calls. But as teams move from prototyping to production API integrations, several limitations surface.

Drawbacks of using Arcade for production AI agent integrations:

• Tool calls only: Arcade is a tool-calling runtime. It does not offer data syncs (for RAG pipelines), webhook ingestion, polling triggers, or unified APIs. If your AI product needs external data continuously kept up to date, or if it must react to events in Salesforce, HubSpot, or other systems, you need a separate platform.

• Narrow first-party catalog: Arcade lists around 24 first-party OAuth providers, which is materially smaller than other platforms in this comparison. Many APIs are only reachable through community MCP servers of varying quality and maintenance.

• MCP-dependent architecture: Every tool call flows through MCP. That is useful for prototyping, but generic MCP servers can reduce reliability in production: broad tool definitions inflate the LLM's context, and handing off multi-step logic to the agent increases hallucination risk.

• Limited observability: Arcade provides basic logs of tool executions. Teams that need full request and response payload inspection, custom log messages inside a tool, or OpenTelemetry export find the logging surface narrow.
  For example: During our testing, we ran a suggested /reddit tool call inside Arcade's Playground. It failed with an invalid Client ID error, but the failed execution never showed up in the Audit Logs page. Small gaps like this point to a platform that is still maturing in production, where several features are described as aspirational or in progress.

• No per-customer configuration: Arcade tools are defined at the server level, not per tenant. There is no built-in support for tenant-specific custom field mappings, per-customer tool behavior, or custom auth validation. Every customer gets the same tool surface.

These constraints are manageable for chat assistants and prototypes. They become real limits when AI agents are a core product feature that must run reliably across customers.

Best Arcade.dev alternatives

1. Nango

Overview

Nango is an open-source integration platform for AI agents and SaaS products. It provides a unified interface for API auth, custom tool calls, data syncs, webhooks, and an MCP server, all on a single platform.

Nango supports 700+ APIs out of the box and is used by hundreds of fast-growing AI agent companies as core infrastructure for their API integrations.

Best for

Teams building production AI agent API integrations that need tool calls, data syncs for RAG, webhooks, and auth across a wide range of APIs on a single code-first platform.

Pros

• Broad API coverage across 700+ APIs: Pre-built auth for OAuth, API keys, JWT, basic auth, and the new MCP Auth standard. White-label by default, so end users authorize your app, not Nango. You can also contribute support for new APIs yourself.

• Code-first with AI coding agent support: Tool definitions are functions that live in your git repo and deploy through CI/CD. The Nango AI Integration Builder works with Claude Code, Cursor, Codex, or any AI coding assistant, so you can generate and iterate on custom tools, syncs, and webhook handlers in minutes.

  # Install the Nango skills for your coding agent
  npx skills add NangoHQ/skills

  <!-- Sample prompt -->

  Build a Nango sync that fetches events from the primary Google Calendar.

  Should run hourly, backfill on initial sync for the last 30 days and
  all future events. After the first run, only fetch future events
  incrementally.

  Return at least:
  - Event title
  - Start and end date
  - Location
  - RSVP status
  - Attendees list (email, display name, response status)

• Open-source, customizable tools: Nango's pre-built integration templates are open source. You can clone an existing tool, modify it for your use case with a coding agent, and deploy it to your account. This is the opposite of the closed tool model used by many MCP-first platforms.

• Built-in MCP server: Nango exposes your custom tool calls through an MCP server. The flow is Agent to Nango MCP to your own custom tools. That keeps the agent's context focused on the specific tools you have built instead of flooding it with hundreds of generic ones.

• Beyond tool calls, on the same platform: Native resumable data syncs (for RAG), webhook processing, polling triggers, and per-customer configuration. A built-in Playground lets you test tool calls, syncs, and triggers interactively before wiring them into your agent, and role-based access control (RBAC) scopes access across teammates.

  

• Deep real-time observability: Every operation generates detailed logs with full API request and response details, error messages, and custom log messages. Everything exports via OpenTelemetry.

  

• Scalable runtime with low overhead: Nango adds less than 100ms overhead on tool calls, isolates each customer's executions with tenant-level fairness, and auto-scales under webhook bursts.

• Enterprise-grade compliance: SOC 2 Type II, GDPR, and HIPAA compliant. Enterprise self-hosting and VPC deployments available.

2. Composio

Overview

Composio is an AI agent integration platform with a catalog of 500+ apps. It acts as an MCP gateway: every integration is automatically exposed through a standardized MCP interface, on top of managed OAuth and pre-built tool definitions.

Best for

Teams building internal or personal automation agents that want an MCP-native alternative to Arcade with a larger pre-built catalog and managed auth, and that do not need data syncs, webhooks, or per-customer configuration.

Pros

• Larger catalog than Arcade: Pre-built tool definitions across 500+ apps, covering Slack, GitHub, Notion, Gmail, Salesforce, and more.

• MCP gateway: Every integration is auto-exposed through MCP so you can expose tools to MCP-Compatible clients (like Claude Desktop, Cursor)
  

• Managed OAuth: Handles token acquisition, refresh, and scope management out of the box.

• Broad framework support: Works with LangChain, CrewAI, OpenAI Agents SDK, and the Vercel AI SDK.

Cons

• Closed-source tools: You cannot inspect or modify the code of Composio's pre-built tools. If a tool does not match your requirements, you build a replacement from scratch outside the platform.
• No data syncs or webhooks: Composio focuses on tool calls. RAG pipelines that need continuously updated external data, or agents that react to real-time events, require a separate system.
• Limited per-customer configuration: Every customer gets the same tool behavior. Tenant-specific field mappings, custom auth validation, or per-customer tool logic are not supported.
• Observability constraints: Basic execution logs. Custom log messages inside tool code and OpenTelemetry export are limited compared to code-first platforms.

3. Pipedream Connect

Overview

Pipedream Connect is the embedded version of Pipedream's serverless integration platform. It exposes MCP servers per app and gives agents access to a large library of pre-built actions across 2,800+ apps.

Best for

Teams that prefer a low-code workflow builder and need wide catalog coverage for internal-facing or lightly customized agent use cases.

Pros

• Large action library: 10,000+ pre-built actions across 2,800+ apps give agents a wide default surface area.
• MCP server per app: Dedicated MCP servers per supported app, so agents can discover and call tools through the protocol.
• Low-code workflow builder: Useful for teams that want to assemble multi-step tool-call logic visually.

Cons

• Acquired by Workday: Pipedream was acquired by Workday (an Enterprise HR platform) in November 2025. You can read their announcement here.
• Non-standard action schemas: Action inputs use Pipedream-specific types ("alert props," "dynamic props," "external props") that require a learning curve and limit compatibility with external tooling.
• Complex action configuration: Most actions must be "configured" before they can run, often requiring 2-5 additional API requests. That adds latency and friction for background agents.
• No data syncs: Pipedream Connect does not offer scheduled or incremental data syncs, so RAG implementations need another platform for ongoing data ingestion.
• Limited white-label auth: End users see Pipedream branding and consent to Pipedream during OAuth, which is a problem for enterprise-facing products.

4. Merge Agent Handler

Overview

Merge Agent Handler is a separate product from Merge's traditional unified API. It lets teams create custom MCP servers with specific pre-built Merge integrations enabled, giving an AI agent a defined set of capabilities.

Best for

Teams that only need pre-built MCP tool-packs for common SaaS actions (for example, fetch tickets from Linear, create an issue in GitHub) and do not need custom tool calls, data syncs, or custom object and field support for CRM and ERP integrations.

Pros

• Pre-built tool-packs: Bundle relevant integrations for a specific agent and restrict the available tools, for example a read-only tool-pack for ticketing.
• Playground: A testing environment to validate MCP behavior before deploying.
• Public MCP import: You can import any public MCP server and edit tool schemas to fit your agent.

Cons

• Narrow connector library: Merge Agent Handler supports around 110 pre-built connectors. If the API you need is not covered, you fall back to public MCP servers.
• No custom tool calls: You cannot build custom tool logic on the platform. Agents are constrained to the pre-built surface, which can force the LLM to chain multiple tool calls for a single business action.
• No Custom fields support: Pre-built tools do not handle custom fields or objects well, which is common in enterprise Salesforce or HubSpot deployments.
• No data syncs: No support for continuous data syncs, so RAG pipelines need a second platform.
• MCP Auth gaps: Some APIs, such as HubSpot's remote MCP server, require MCP Auth. Merge Agent Handler currently supports standard (non-MCP) auth for most providers.

Comparison of Arcade.dev alternatives

Feature	Nango	Composio	Pipedream Connect	Merge Agent Handler
Primary focus	Agentic, code-first AI agent and product integrations	MCP-first tool calling	Low-code embedded workflows	Pre-built MCP tool-packs
Supported APIs	700+	500+	2,800+	~110
Tool customization	Full (code-first, open source)	Limited (closed tools)	Low-code workflows	No custom tool code
AI agent (LLM) tool calls	Yes (custom, code-first)	Yes (pre-built)	Yes (pre-built actions)	Yes (pre-built)
AI coding agent support (Claude Code, Cursor)	Yes (optimized tools and skills)	No	No	No
MCP server	Yes (on your custom tools)	Yes (auto on all tools)	Yes (per app)	Yes
Data syncs for RAG	Yes (native, incremental)	No	No	No
Webhook processing	Yes (high throughput)	No	Triggers only	No
Per-customer configuration	Yes	Limited	Limited	Limited
Observability	Deep (OpenTelemetry, custom logs)	Basic	Basic	Basic
Auth model	White-label (your brand)	Managed	Pipedream-branded	Platform-managed
Open source	Yes	Partial (closed tools)	Partial	No
Self-hosting	Yes (Enterprise)	No	No	No

How we evaluated these platforms

We assessed each Arcade.dev alternative across five dimensions that matter for production AI agent integrations:

1. Catalog breadth and extensibility: How many APIs are supported out of the box? Can you add new APIs yourself without waiting on the vendor?
2. Tool customization: Can you build and modify tool logic in code? Can AI coding agents (Claude Code, Cursor, Codex) help generate or refactor tools?
3. Integration patterns beyond tool calls: Does the platform support data syncs for RAG, webhooks, polling triggers, and per-customer configuration?
4. Observability: Are there full request and response logs, custom log messages inside tool code, and OpenTelemetry export?
5. Deployment and auth model: Is auth white-label and tenant-safe? Is self-hosting available for regulated workloads?

Which alternative should you choose?

You are building production AI agent integrations with broad requirements: Choose Nango. It is the only platform in this comparison that combines pre-built tool calls, data syncs, webhooks, and unified APIs on a single code-first platform, with 700+ APIs and AI coding agent support for building custom tools fast.

You want an MCP-native alternative to Arcade with a larger catalog: Consider Nango or Composio. They both give you pre-built tools behind an MCP gateway.

You prefer a low-code workflow builder with a large catalog: Pipedream Connect fits, especially for internal-facing agents.

You only need standard, pre-built tool-packs: Merge Agent Handler can work for ticketing, CRM reads, and other common SaaS actions. Confirm that your APIs are supported and that you do not need data syncs or deep customization.

FAQ

What is the best Arcade.dev alternative for production AI agents?

Nango is a strong fit for teams building production AI agent API integrations. It supports 700+ APIs, code-first custom tool calls with AI coding agent support, data syncs for RAG, webhooks, and deep observability with OpenTelemetry. Unlike Arcade, it is not limited to tool calls and exposes an MCP server on top of your own custom tools instead of relying on public MCP servers.

Does Arcade.dev support data syncs or webhooks?

No. Arcade.dev is a tool-calling runtime. It does not provide scheduled or incremental data syncs, webhook ingestion, or polling triggers. If your AI agent needs continuously updated external data for a RAG pipeline, or must react to events in Salesforce or HubSpot, you need a separate platform. Nango supports all of these on a single platform alongside tool calls.

Is Arcade.dev open source?

Arcade.dev's SDK and MCP server framework are open source, so you can build custom MCP servers and self-host. The platform itself (runtime, catalog, managed auth) is a hosted product. Nango, by contrast, is fully open source on GitHub, and all of its pre-built integration templates are open and editable.

Can I use Arcade.dev alternatives with LangChain, CrewAI, or the OpenAI Agents SDK?

Yes. Nango, Composio, Pipedream Connect, and Merge Agent Handler all expose tools through standard interfaces (REST APIs and/or MCP servers) that work with any agent framework. Nango's MCP server and REST API integrate with LangChain, CrewAI, OpenAI Agents SDK, Vercel AI SDK, and Mastra. Composio is MCP-native and works with any MCP-compatible client.

Can I build custom tools with Arcade.dev alternatives using AI coding agents?

No, not with Arcade itself. But Nango is designed for this: tool definitions are code, and the Nango AI Integration Builder provides skills for Claude Code, Cursor, and other coding assistants to generate and refine tool calls, data syncs, and webhook handlers. Composio, Arcade, Pipedream Connect, and Merge Agent Handler do not ship dedicated AI coding agent integrations for building tools on their platforms.

Conclusion

Arcade.dev is a focused MCP runtime that fits teams with strict MCP-first requirements and simple tool-calling workloads. Once AI agent integrations become a core product surface, the tool-calling-only scope, narrow first-party catalog, and basic observability start to matter.

Nango covers the broadest set of production requirements on a single platform: 700+ APIs, custom tool calls, data syncs for RAG, webhooks, unified APIs, and deep observability, with AI coding agent support for building everything fast. Composio is a closer direct alternative to Arcade if your scope stays inside MCP tool calls. Pipedream Connect and Merge Agent Handler cover narrower low-code and pre-built use cases.

Start with the hardest integration requirement in your product roadmap. The platform that handles it today will carry you further as your AI agents scale.

Related reading:

• How to build reliable tool calls for AI agents
• Best practices for building API integrations with AI agents
• Best AI agent integration platforms
• Best AI agent authentication platforms
• Best Composio alternatives for AI agent integrations
• Best Pipedream Connect alternatives for AI integrations