I've been running OpenClaw on a Hostinger VPS for about a month now, and it has fundamentally changed how I work. What started as "let me try this AI agent thing" turned into a powerful assistant that saves me hours every week by automating routine tasks — from GitHub issue triage to email management.
OpenClaw doesn't do everything for me (yet), but it handles a lot of the repetitive work that used to eat up my day. Here's a deep dive into every use case I've discovered so far.
What is OpenClaw?
OpenClaw is an open-source AI agent platform that runs on your own infrastructure. You connect it to your chat channels (Telegram, WhatsApp, Discord), give it access to your tools, and it becomes a persistent assistant that remembers context across sessions. Think of it as your own self-hosted AI employee that's always on.
My setup: Docker container on a Hostinger VPS, with Telegram as my primary interface. Most of my interactions — voice messages, text, files — go through Telegram. It feels like texting a colleague who never sleeps.
Use Case 1: Autonomous GitHub Issue Management
This is the killer feature for me. OpenClaw monitors my HalloCasa repositories every 2 hours via a heartbeat. When a new issue appears, it:
- Notifies me on Telegram
- Generates a detailed implementation plan using Cursor CLI with Claude Opus for planning
- Posts the plan as a comment on the GitHub issue
- Waits for my approval before implementing
- Implements the fix using Cursor CLI with Composer
- Creates a branch, commits, pushes, and opens a PR
In the first week alone, it planned and implemented fixes for currency display bugs, locale changes, phone validation, and filter cleanup — all with minimal intervention from me.
The workflow follows the "Factory" pattern I heard about at Agentic Conf Hamburg: don't just use AI to build features — build a production line that builds features for you.
Use Case 2: Email Management
OpenClaw reads and sends emails via Himalaya CLI (IMAP/SMTP). I just tell it what to do on Telegram:
- "Tell the sports group leader we can't come today" → Searched my contacts, found the match, sent a polite cancellation.
- "Email my tax advisor that I need to reschedule" → Found the firm in contacts, sent a professional German email.
- "Reply to the kindergarten about scheduling a visit" → Continued an existing email thread with context-aware reply.
It sends HTML emails with a professional signature and handles German and English.
Use Case 3: Morning Briefing (Cron Job)
Every morning at 7:00 AM (my timezone, Europe/Berlin), OpenClaw runs an automated check:
- Scans unread emails from the last 24 hours
- Checks yesterday's emails for pending follow-ups
- Cross-references with my Google Calendar for today and tomorrow
- Sends me a concise summary on Telegram
This runs on Claude Haiku (cheap) and costs almost nothing. I wake up to a briefing instead of manually checking three different apps.
Use Case 4: Calendar Management
OpenClaw has full access to my Google Calendar via OAuth. Examples:
- Conference schedule : I sent a PDF of the Agentic Conf Hamburg schedule with sessions I'd marked with red boxes. It extracted the image, identified the marked sessions using vision AI, fetched details from the conference website, and created 9 calendar events with full descriptions, speaker info, and links.
- Creating meetings : "Create a meeting with Phillip P. for today at 18:00 CET" → Done.
Use Case 5: Contact Lookup
Connected to my iCloud contacts via CardDAV, OpenClaw searches by name, organization, or context. When I say "email the sports group leader," it finds the match and uses the right email. No manual lookup needed.
Use Case 6: LinkedIn Post Drafting
I've used it to draft LinkedIn posts for:
- AWS Community Day Athens 2026 : Looked up all speakers from the conference website, compiled them alphabetically, created a professional announcement post.
- Agentic Conf Hamburg recap : Searched for organizers' backgrounds, found LinkedIn profiles, referenced specific talks, and wove in my personal highlights about the "Factory" concept.
It does the research, I do the personal touch.
Use Case 7: Research & Due Diligence
Questions that would normally cost 15 minutes of Googling:
- "Is there an app for biometric passport photos with QR codes?" → Comparison of available apps, including recent regulation changes.
- "There's a conference in my area tomorrow, what is it?" → Found the event, full program, speakers, venue, and registration link.
Use Case 8: Document Generation
- Birthday invitation : Generated a themed HTML invitation card with embedded images and QR code, published as a shareable link.
- Application form : Built a bilingual job application form, deployed to GitHub Pages so it works when shared via WhatsApp.
- Kindergarten applications : Generated PDF application forms from templates.
- Email signatures : Set up HTML signatures in Gmail (via API) and Apple Mail.
Use Case 9: Workspace & Config Management
OpenClaw manages its own configuration:
- Version-controls its workspace files in a Git repo
- Adjusts its own heartbeat intervals and model settings when I ask
- Maintains daily memory notes and long-term memory files for context continuity
Use Case 10: Global Brain via PeachBase
OpenClaw is connected to PeachBase — a serverless vector database that acts as my persistent memory across all AI agents. Via MCP, OpenClaw can store and retrieve knowledge: personal info, project decisions, contacts, learnings.
When I tell OpenClaw something worth remembering, it stores it in PeachBase. When I ask a question weeks later — even from a different agent like Cursor — the knowledge is there. It's the shared brain that ties everything together.
I wrote a dedicated post about this: My Global Brain with PeachBase.
Use Case 11: Multi-Channel Communication
I talk to OpenClaw primarily via Telegram, but it also:
- Sends emails on my behalf (Himalaya/SMTP)
- Is connected to WhatsApp
- Can deliver cron job results to specific Telegram chats
Use Case 12: Writing This Blog Post
Meta moment: this very blog post was drafted by OpenClaw. I sent a voice message on Telegram (in German): "I want to write about OpenClaw and how I've been using it — go through all your history and find the use cases, in English please."
It scanned 23 days of daily memory notes, extracted every use case, researched the blog repo format, and produced a full draft in the right Gatsby frontmatter format — all in one turn. I just reviewed and tweaked.
This is the "Factory" idea in action: I didn't write a blog post. I told my agent to write one, and it had all the context it needed because it was there for every use case.
Security: It's a Spectrum
Giving an AI agent access to your email, contacts, calendar, and GitHub is powerful — but it's also a security conversation you need to have with yourself.
OpenClaw treats security as a spectrum, not a binary. You can start wide-open for convenience and tighten as you go. Here's what's available and what I use:
Sandboxing
OpenClaw supports Docker-based sandboxing where tool execution (shell commands, file reads/writes) runs inside an isolated container instead of directly on the host. You can choose:
-
"off"— everything runs on the host (my current setup, maximum convenience) -
"non-main"— only non-main sessions (group chats, webhooks) are sandboxed -
"all"— every session runs sandboxed
I'm still on "off" because I'm the only user and I trust the agent boundary. But if you're running OpenClaw on a shared machine or exposing it to group chats, sandboxing is a must.
Tool Policy
You can allowlist or denylist specific tools per agent. For example, you could disable exec (shell access) entirely and only allow read/write — or restrict which commands can run. OpenClaw also has an elevated exec model (think sudo) where dangerous commands require explicit approval.
Secrets
One thing I'd do differently: my early setup had API keys in config files. OpenClaw supports environment variables and secret refs instead. Move your credentials out of plaintext config.
The Human-in-the-Loop Rule
My most important security measure isn't technical — it's a rule in my agent's config: always ask before sending emails. After one incident where the agent sent an email I hadn't approved, I added a hard rule. The agent now shows me a draft and waits for "OK" before any outbound communication. This applies to anything that "leaves the machine" — emails, social posts, webhooks.
Network
The Gateway port (18789) should never be public. Mine is localhost-only inside Docker. If you need remote access, use Tailscale or an authenticated reverse proxy with TLS.
My Take
Security with AI agents is genuinely new territory. The threat model is different from traditional apps because the agent can be influenced by external content (prompt injection via emails, web pages). OpenClaw has tools to limit blast radius — sandboxing, tool policies, approval gates — but the most important thing is being deliberate about what you give access to and expanding gradually.
The Numbers
After a month of use, here's what surprised me:
- Cost optimization matters : Running on Claude Opus 4.6 burns through API credits fast. Switching heartbeats to Haiku and reducing intervals from 30min to 2h made a huge difference.
- Memory is everything : The daily notes + MEMORY.md system means I never have to re-explain context. It knows my projects, my contacts, my preferences.
- HTML email was harder than expected : Getting Himalaya to send proper HTML emails with MML syntax took some trial and error. Plain text signatures don't have clickable links.
What's Next
- Blog post automation : Using OpenClaw to help draft and publish posts (like this one!)
- Deeper GitHub integration : Auto-implementing approved plans without manual trigger
- More cron jobs : Weather briefings, social media monitoring, calendar reminders
Conclusion
OpenClaw isn't just a chatbot. It's a personal operating system that happens to be powered by AI. The combination of persistent memory, tool access (email, calendar, contacts, GitHub, file system), and multi-channel communication makes it genuinely useful — not in a "cool demo" way, but in a "I saved 2 hours today" way.
If you're a developer comfortable with Docker and CLI tools, I highly recommend giving it a try. The learning curve is worth it.
Links:
🚀 I'm also looking for beta testers for PeachBase — the serverless vector DB I use as shared memory across all my AI agents. If you want to try it, sign up!
Thanks for reading! If you have questions about my setup, feel free to reach out. And if you'd like help setting up your own OpenClaw AI agent — whether it's configuration, tool integration, or building custom workflows — I'm available for consulting. Just drop me a message at office@martinmueller.dev or book a call at calendly.com/martinmueller_dev.
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