Files
n8n-mcp/docs/IMPLEMENTATION_ROADMAP.md
czlonkowski 078b67ff35 Implement SQLite database with full-text search for n8n node documentation
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>
2025-06-07 21:12:17 +00:00

4.8 KiB

n8n-MCP Implementation Roadmap

Completed Features

1. Core MCP Server Implementation

  • Basic MCP server with stdio transport
  • Tool handlers for n8n workflow operations
  • Resource handlers for workflow data
  • Authentication and error handling

2. n8n Integration

  • n8n API client for workflow management
  • MCP<->n8n data bridge for format conversion
  • Workflow execution and monitoring

3. Node Source Extraction

  • Extract source code from any n8n node
  • Handle pnpm directory structures
  • Support for AI Agent node extraction
  • Bulk extraction capabilities

4. Node Storage System

  • In-memory storage service
  • Search functionality
  • Package statistics
  • Database export format

🚧 Next Implementation Steps

Phase 1: Database Integration (Priority: High)

  1. Real Database Backend

    • Add PostgreSQL/SQLite support
    • Implement proper migrations
    • Add connection pooling
    • Transaction support
  2. Enhanced Storage Features

    • Version tracking for nodes
    • Diff detection for updates
    • Backup/restore functionality
    • Data compression

Phase 2: Advanced Search & Analysis (Priority: High)

  1. Full-Text Search

    • Elasticsearch/MeiliSearch integration
    • Code analysis and indexing
    • Semantic search capabilities
    • Search by functionality
  2. Node Analysis

    • Dependency graph generation
    • Security vulnerability scanning
    • Performance profiling
    • Code quality metrics

Phase 3: AI Integration (Priority: Medium)

  1. AI-Powered Features

    • Node recommendation system
    • Workflow generation from descriptions
    • Code explanation generation
    • Automatic documentation
  2. Vector Database

    • Node embeddings generation
    • Similarity search
    • Clustering similar nodes
    • AI training data export

Phase 4: n8n Node Development (Priority: Medium)

  1. MCPNode Enhancements

    • Dynamic tool discovery
    • Streaming responses
    • File upload/download
    • WebSocket support
  2. Custom Node Features

    • Visual configuration UI
    • Credential management
    • Error handling improvements
    • Performance monitoring

Phase 5: API & Web Interface (Priority: Low)

  1. REST/GraphQL API

    • Node search API
    • Statistics dashboard
    • Webhook notifications
    • Rate limiting
  2. Web Dashboard

    • Node browser interface
    • Code viewer with syntax highlighting
    • Search interface
    • Analytics dashboard

Phase 6: Production Features (Priority: Low)

  1. Deployment

    • Kubernetes manifests
    • Helm charts
    • Auto-scaling configuration
    • Health checks
  2. Monitoring

    • Prometheus metrics
    • Grafana dashboards
    • Log aggregation
    • Alerting rules

🎯 Immediate Next Steps

  1. Database Integration (Week 1-2)

    // Add to package.json
    "typeorm": "^0.3.x",
    "pg": "^8.x"
    
    // Create entities/Node.entity.ts
    @Entity()
    export class Node {
      @PrimaryGeneratedColumn('uuid')
      id: string;
    
      @Column({ unique: true })
      nodeType: string;
    
      @Column('text')
      sourceCode: string;
      // ... etc
    }
    
  2. Add Database MCP Tools (Week 2)

    // New tools:
    - sync_nodes_to_database
    - query_nodes_database
    - export_nodes_for_training
    
  3. Create Migration Scripts (Week 2-3)

    npm run migrate:create -- CreateNodesTable
    npm run migrate:run
    
  4. Implement Caching Layer (Week 3)

    • Redis for frequently accessed nodes
    • LRU cache for search results
    • Invalidation strategies
  5. Add Real-Time Updates (Week 4)

    • WebSocket server for live updates
    • Node change notifications
    • Workflow execution streaming

📊 Success Metrics

  • Extract and store 100% of n8n nodes
  • Search response time < 100ms
  • Support for 10k+ stored nodes
  • 99.9% uptime for MCP server
  • Full-text search accuracy > 90%

🔗 Integration Points

  1. n8n Community Store

    • Sync with community nodes
    • Version tracking
    • Popularity metrics
  2. AI Platforms

    • OpenAI fine-tuning exports
    • Anthropic training data
    • Local LLM integration
  3. Development Tools

    • VS Code extension
    • CLI tools
    • SDK libraries

📝 Documentation Needs

  • API reference documentation
  • Database schema documentation
  • Search query syntax guide
  • Performance tuning guide
  • Security best practices

This roadmap provides a clear path forward for the n8n-MCP project, with the most critical next step being proper database integration to persist the extracted node data.