This project provides a Model Context Protocol (MCP) server that bridges n8n's workflow automation platform with AI assistants like Claude. It offers AI deep knowledge of n8n's 532 nodes, their properties, documentation, and operations, enabling AI to build and manage n8n workflows.

How It Works

n8n-MCP pre-builds a database of n8n node information, including properties, documentation, and AI capabilities. This structured data is then served via an MCP-compatible server, allowing AI models to query and understand n8n nodes. The project emphasizes a "validate before building" approach for AI-generated workflows, offering tools to check node configurations and workflow structures for accuracy and completeness.

Quick Start & Requirements

• npx: npx n8n-mcp (requires Node.js)
• Docker: docker pull ghcr.io/czlonkowski/n8n-mcp:latest (requires Docker)
• Local Install: Clone repo, npm install, npm run build, npm run rebuild, npm start (requires Node.js, Git)
• Configuration: Requires integration with AI assistants like Claude Desktop via claude_desktop_config.json. Optional n8n API credentials for workflow management.
• Setup Time: ~5 minutes for npx or Docker.
• Docs: n8n-MCP

Highlighted Details

• 100% node coverage, 98.7% property coverage, 88% documentation coverage.
• Provides "essential properties" (10-20 key fields) for AI efficiency.
• Includes n8n workflow management tools (create, update, execute) via optional API credentials.
• Offers robust validation tools for node configurations and entire workflows.

Maintenance & Community

The project is actively maintained by czlonkowski. Sponsorships are encouraged to support development. Links to documentation and guides are provided.

Licensing & Compatibility

MIT License. Free for commercial use and closed-source linking, with attribution appreciated.

Limitations & Caveats

AI-generated workflows require careful validation and testing in development environments before production deployment due to potential unpredictability. The project warns against directly editing production workflows with AI.