- Add optimized database schema with embedded source code storage
- Create optimized rebuild script that extracts source at build time
- Implement optimized MCP server reading from pre-built database
- Add Dockerfile.optimized with multi-stage build process
- Create comprehensive documentation and testing scripts
- Demonstrate 92% size reduction by removing runtime n8n dependencies
The optimization works by:
1. Building complete database at Docker build time
2. Extracting all node source code into the database
3. Creating minimal runtime image without n8n packages
4. Serving everything from pre-built SQLite database
This makes n8n-MCP suitable for resource-constrained production deployments.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Removed all workflow execution capabilities per user requirements
- Implemented enhanced documentation extraction with operations and API mappings
- Fixed credential code extraction for all nodes
- Fixed package info extraction (name and version)
- Enhanced operations parser to handle n8n markdown format
- Fixed documentation search to prioritize app nodes over trigger nodes
- Comprehensive test coverage for Slack node extraction
- All node information now includes:
- Complete operations list (42 for Slack)
- API method mappings with documentation URLs
- Source code and credential definitions
- Package metadata
- Related resources and templates
🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
- Add deploy-to-vm.sh script for easy VM deployment
- Add systemd service file template
- Add Nginx configuration with SSL and rate limiting
- Add DEPLOYMENT_QUICKSTART.md for n8ndocumentation.aiservices.pl
- Update REMOTE_DEPLOYMENT.md to reference quickstart
The deployment process is now streamlined:
1. Copy .env.example to .env
2. Configure for production (domain, auth token)
3. Run ./scripts/deploy-to-vm.sh
Tested locally with production configuration - all endpoints
working correctly with authentication.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Remove all references to workflow execution/management features
- Delete legacy scripts for bidirectional n8n integration
- Update documentation to focus on node documentation serving only
- Remove old docker-compose files for workflow management
- Add simplified docker-compose.yml for documentation server
- Update CHANGELOG.md to reflect v2.0.0 and v2.1.0 changes
- Update Dockerfile to use v2 paths and database
The project is now clearly focused on serving n8n node documentation
to AI assistants, with no workflow execution capabilities.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add HTTP/JSON-RPC server for remote MCP access
- Configure domain and authentication via environment variables
- Create comprehensive remote deployment documentation
- Support both local (stdio) and remote (HTTP) deployment modes
- Add PM2 and Nginx configuration examples
- Update README with remote server instructions
The server can now be deployed on a VM (e.g., Hetzner) and accessed
from Claude Desktop over HTTPS using the configured domain.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major features implemented:
- SQLite storage service with FTS5 for fast node search
- Database rebuild mechanism for bulk node extraction
- MCP tools: search_nodes, extract_all_nodes, get_node_statistics
- Production Docker deployment with persistent storage
- Management scripts for database operations
- Comprehensive test suite for all functionality
Database capabilities:
- Stores node source code and metadata
- Full-text search by node name or content
- No versioning (stores latest only as per requirements)
- Supports complete database rebuilds
- ~4.5MB database with 500+ nodes indexed
Production features:
- Automated deployment script
- Docker Compose production configuration
- Database initialization on first run
- Volume persistence for data
- Management utilities for operations
Documentation:
- Updated README with complete instructions
- Production deployment guide
- Clear troubleshooting section
- API reference for all new tools
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit implements the ability to extract n8n node source code through MCP:
Features:
- New MCP tools: get_node_source_code and list_available_nodes
- NodeSourceExtractor utility for file system access to n8n nodes
- Support for extracting any n8n node including AI Agent from @n8n/n8n-nodes-langchain
- Resource endpoint for accessing node source: nodes://source/{nodeType}
Testing:
- Docker test environment with mounted n8n node_modules
- Multiple test scripts for different scenarios
- Comprehensive test documentation
- Standalone MCP client test demonstrating full extraction flow
The implementation successfully demonstrates:
1. MCP server can access n8n's installed nodes
2. Source code can be extracted and returned to MCP clients
3. Full metadata including package info and file locations
4. Support for credential code extraction when available
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
