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n8nClaw

shabbirun/n8nclaw

healthy GitHub

A visual workflow recreation of OpenClaw built entirely in n8n, trading code complexity for drag-and-drop accessibility. It's the "no-code" cousin that runs multi-channel AI agents through Postgres memory and Supabase RAG without writing a single line of code.

Decision Block

Why choose n8nClaw over OpenClaw?

Quick recommendation layer first, deeper analysis second. Use this before diving into metrics and architecture details.

Recommendation Layer
Compare with OpenClaw
Why choose this
  • Recommendation signal still sparse. Use the compare view and source links before making a call.
Tradeoffs
  • Still less proven than OpenClaw in maturity, docs depth, or production mileage.
Best fit
  • Security-sensitive self-hosters
Avoid if
  • You only want battle-tested projects with a long public track record
Confidence / Evidence
Mixed Evidence 35%
Freshly Reviewed
Quick Refresh

Limited evidence available. Use the primary sources before making a production decision.

AI decision layer last reviewed Apr 20, 2026. Helpful, but still inference-heavy enough to double-check primary sources.

Last generated Mar 13, 2026
Last reviewed Apr 20, 2026
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Source window: GitHub metadata, README, recent commits, latest release, Reddit, Brave search

Measured Security
72
Measured Memory
85 MB
GitHub Stars
225
Boot Time
250 ms
Memory
85 MB
Language
TypeScript

Community Pulse

78% Positive
1 Reddit Mentions

Security Radar

Security radar summary for n8nClaw.

  • n8nClaw: Sandboxing 5 of 10, API Security 6 of 10, Network Isolation 5 of 10, Telemetry Safety 7 of 10, Shell Protection 7 of 10.

Evaluation Scale: 10 = Maximum Safety / 1 = High Risk

Star Growth (2026)

Star history summary.

  • n8nclaw: 104 recorded points. From 14 stars on 2026-01-01 to 225 on 2026-04-21.

ClawVerse News

Latest articles and global buzz

No news data available at the moment.
Last Scan: 4/21/2026, 12:16:09 PM
#n8n-workflow #multi-channel #visual-automation #self-hosted #rag-memory

n8nClaw: OpenClaw Reimagined as a Visual Workflow

n8nClaw is a fascinating reimplementation of OpenClaw's core functionality built entirely within the n8n automation platform. Rather than running as a standalone application, n8nClaw operates as a visual workflow that orchestrates AI agents through n8n's node-based interface. The architecture supports multi-channel messaging (Telegram, WhatsApp, Gmail) with a central Claude Sonnet 4.5 agent handling all interactions via OpenRouter.

Core Architecture & Differentiation from OpenClaw

The system uses Postgres for chat memory (15-message context window) and implements a sophisticated memory pipeline that aggregates, summarizes (using Claude Haiku), embeds (via OpenAI), and stores conversations in Supabase's vector database for long-term retrieval. Unlike OpenClaw's skill-based plugin system, n8nClaw uses sub-agents (Worker 1-3) for tasks like research, email management, and document handling. The hourly heartbeat trigger enables autonomous task processing similar to OpenClaw's scheduled operations, but configured through n8n's cron-style scheduling nodes.

Trade-offs & Considerations

While n8nClaw eliminates the need to write code, it inherits n8n's resource overhead and requires familiarity with n8n's workflow paradigm. Security depends on proper n8n instance configuration—unlike OpenClaw's documented security issues with exposed dashboards, n8nClaw's security posture is tied to how well the underlying n8n deployment is hardened. The project is ideal for users who prefer visual workflow builders over terminal-based configuration and already have n8n in their infrastructure stack.

Live Data Partner OpenClaw Seismograph
Threat Level elevated