I have recreated OpenClaw in n8n. And I am making it available as a community project! Maybe it will turn into a real community project
n8n-claw contains the following:
• n8n & Supabase
• the “OpenClaw” workflows (MCP Builder, Workflow Builder, etc.)
• Setup script that installs everything on a fresh VPS, sets up Supabase tables, pulls SSL certificates, and prepares everything
I tried to make the installation as simple as possible:
Clone the Github repository & run the setup script
Query the setup for n8n API key, Telegram token, Telegram user ID, and desired n8n-claw personality (Image 4)
Set up the database and n8n
Output the credentials for the Supabase database connection to n8n (not possible automatically).
Only the LLM API key & Supabase data need to be entered as credentials and all workflows published. Then you can start chatting right away (images 2+3).
I would be very excited to see this project developed further. So far, only a framework has been created, so there is certainly still a lot of potential to be tapped. I invite you to test, expand, optimize, improve, etc. n8n-claw, and I would be very happy if you would collaborate on this and we could succeed in building an AI agent in n8n that is as autonomous as possible.
Not because OpenClaw and Co. aren’t cool, but because here, even for non-programmers, we can create a basis for a system that is also comprehensible to them.
The repo already contains a Claude.md so you can work with Claude Code, etc.
n8n-claw Update: Memory Behavior and Consolidation (RAG Pipeline) for long-term memory and embeddings
Memory Behavior:
The agent actively stores preferences, habits, corrections, and important facts about the user
Before making recommendations or responding, it searches its long-term memory for relevant information
It references past conversations when appropriate (“You said last week…”)
If you correct it, it permanently remembers the correction
It does not ask for information it has already stored
RAG Pipeline (Memory Consolidation):
Runs automatically every day at 3:00 a.m.
Reads all new entries from memory_daily (daily log of all conversations)
Summarizes them into compact summaries using the LLM
Generates an embedding vector for each summary (OpenAI, Voyage AI, or Ollama)
Stores summary + vector in memory_long — the long-term memory
Enables semantic search: the agent finds memories by meaning, not just by exact keywords
This enables Hashtag#n8n-claw to get to know the user and retain their preferences, projects, ideas, etc. in the long term (similar to what OpenClaw does, only via a (vector) database, not via Markdown files)!
And now for the next n8n-claw update: Heartbeat (proactive tasks) and task management.
There are a few new features:
- Task Management: Create, list, and complete tasks via Telegram. With priorities (urgent/high/medium/low), due dates, and subtasks. “Remind me of X” now creates both: a reminder and a task.
- Heartbeat: The agent checks every 15 minutes to see if there are any open tasks and proactively notifies you via Telegram if something is pending. It is automatically activated if you select “proactive” during installation.
Morning Briefing: Daily summary via Telegram at a configurable time. Can be activated via chat, e.g., “Activate Morning Briefing at 9 a.m.”
And once again, a few new features for n8n-claw: media handling, self-hosted web search, and onboarding
#n8n-claw now has media handling and can:
- Process/recognize images (e.g., what is in the picture, where is it, etc.)
- Process location (knows where I am and can provide context/information)
- Process voice messages (out-of-the-box)
- Process PDFs (conversation about the content)
In addition, the first message includes a short onboarding session with the most important features.
I have also integrated #SearXNG as a local search engine, which also works out-of-the-box! I have adapted the MCP Builder so that it uses SearXNG and no longer requires an API key (previously: Brave)!
Thank you Freddy this looks brilliant(I fit into: “non-programmers, we can create a basis for a system that is also comprehensible to them.”) Question for you and others here: In terms of ease of setup, user friendliness, maintenance and cost how would you compare N8n-claw to something like this https://youtu.be/C4fTWiOGXpM?si=JZGI107X7smGX2-8 (Jack Roberts demonstrates how to build a personalized 24/7 AI employee by integrating OpenClaw and Google’s AntiGravity, highlighting seven key use cases including a custom dashboard, automated invoicing, and a sophisticated three-tier memory system.) ?
n8n-claw is my self-hosted OpenClaw in n8n experiment: n8n + Supabase/Postgres for memory, SearXNG for web search, and MCP Builder / workflow builder / reminder / heartbeat workflows. Through Telegram the agent can even build new MCP servers and whole workflows (via the Claude Code integration), so you rarely need to open the n8n UI — the goal is a self-expanding system.
Jack Roberts’ video (OpenClaw + Google AntiGravity) presents a 24/7 “AI employee” with seven use cases (custom dashboard, automated invoicing, three-tier memory, etc.). I don’t know whether Jack ties n8n into his setup, so I can only judge what the video explicitly shows.
Comparison (setup / UX / maintenance / cost):
• Setup: n8n-claw = Docker + wizard, then mostly using telegram. AntiGravity needs OpenClaw, Google’s AntiGravity access, and his template.
• Usability: n8n gives you low-code nodes, Supabase UI, plus Telegram commands to extend the system. Jack’s build relies more on his dashboard and prompt flows.
• Maintenance: n8n-claw is open source (updates via ./setup.sh –force). AntiGravity depends on two SaaS vendors.
• Cost: n8n-claw = your own server + API credits you already pay for. AntiGravity stack = OpenClaw plus Google Workspace/AntiGravity.
