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>
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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)
-
Real Database Backend
- Add PostgreSQL/SQLite support
- Implement proper migrations
- Add connection pooling
- Transaction support
-
Enhanced Storage Features
- Version tracking for nodes
- Diff detection for updates
- Backup/restore functionality
- Data compression
Phase 2: Advanced Search & Analysis (Priority: High)
-
Full-Text Search
- Elasticsearch/MeiliSearch integration
- Code analysis and indexing
- Semantic search capabilities
- Search by functionality
-
Node Analysis
- Dependency graph generation
- Security vulnerability scanning
- Performance profiling
- Code quality metrics
Phase 3: AI Integration (Priority: Medium)
-
AI-Powered Features
- Node recommendation system
- Workflow generation from descriptions
- Code explanation generation
- Automatic documentation
-
Vector Database
- Node embeddings generation
- Similarity search
- Clustering similar nodes
- AI training data export
Phase 4: n8n Node Development (Priority: Medium)
-
MCPNode Enhancements
- Dynamic tool discovery
- Streaming responses
- File upload/download
- WebSocket support
-
Custom Node Features
- Visual configuration UI
- Credential management
- Error handling improvements
- Performance monitoring
Phase 5: API & Web Interface (Priority: Low)
-
REST/GraphQL API
- Node search API
- Statistics dashboard
- Webhook notifications
- Rate limiting
-
Web Dashboard
- Node browser interface
- Code viewer with syntax highlighting
- Search interface
- Analytics dashboard
Phase 6: Production Features (Priority: Low)
-
Deployment
- Kubernetes manifests
- Helm charts
- Auto-scaling configuration
- Health checks
-
Monitoring
- Prometheus metrics
- Grafana dashboards
- Log aggregation
- Alerting rules
🎯 Immediate Next Steps
-
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 } -
Add Database MCP Tools (Week 2)
// New tools: - sync_nodes_to_database - query_nodes_database - export_nodes_for_training -
Create Migration Scripts (Week 2-3)
npm run migrate:create -- CreateNodesTable npm run migrate:run -
Implement Caching Layer (Week 3)
- Redis for frequently accessed nodes
- LRU cache for search results
- Invalidation strategies
-
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
-
n8n Community Store
- Sync with community nodes
- Version tracking
- Popularity metrics
-
AI Platforms
- OpenAI fine-tuning exports
- Anthropic training data
- Local LLM integration
-
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.