n8n-mcp/docs/MCP_ACTION_PLAN.md

MCP Implementation Action Plan

Key Insights from Analysis

✅ What You Already Have (Working Well)

1. Excellent property extraction - All properties with complete schemas
2. Proper data structure - Properties include types, options, displayOptions
3. Efficient storage - JSON in SQLite is perfect for this use case
4. Complete metadata - Operations, credentials, documentation all captured

❌ The Real Problem

• Information overload: Returning 200+ properties when AI needs 10-20
• No filtering: All properties returned regardless of relevance
• Poor organization: Essential mixed with advanced properties
• No examples: AI agents need concrete examples to work from

💡 The Solution

Don't restructure - add intelligent filtering layers on top

Immediate Action Plan (This Week)

Day 1-2: Implement get_node_essentials

1. Create services:

   touch src/services/property-filter.ts
   touch src/services/example-generator.ts
   

2. Copy code from implementation guide:

   • PropertyFilter class with essential lists
   • ExampleGenerator with concrete examples
   • Tool implementation in server.ts

3. Test with top 5 nodes:

   • nodes-base.httpRequest
   • nodes-base.webhook
   • nodes-base.code
   • nodes-base.set
   • nodes-base.postgres

4. Measure improvement:

   npm run build
   node scripts/test-essentials.js
   

Day 3: Expand Coverage

1. Add 15 more nodes to ESSENTIAL_PROPERTIES:

   • nodes-base.if
   • nodes-base.merge
   • nodes-base.splitInBatches
   • nodes-base.function
   • nodes-base.email
   • nodes-base.slack
   • nodes-base.github
   • nodes-base.googleSheets
   • nodes-base.openAi
   • nodes-base.redis
   • nodes-base.mongodb
   • nodes-base.mysql
   • nodes-base.ftp
   • nodes-base.ssh
   • nodes-base.executeCommand

2. Create examples for each node

3. Test with AI agents

Day 4-5: Implement search_node_properties

1. Create property flattener:

   // Converts nested properties to flat list with paths
   class PropertyFlattener {
     static flatten(properties: any[], path = ''): FlatProperty[]
   }
   

2. Add search functionality:

   • Search by name
   • Search by description
   • Search by type

3. Test search accuracy

Week 2: Validation & Task Templates

1. Implement validate_node_config:

   • Check required properties
   • Validate against displayOptions
   • Provide helpful error messages

2. Create task templates:

   • Common API patterns
   • Database operations
   • File handling
   • Webhook patterns

Essential Property Lists (Starting Point)

// Top 20 nodes to optimize first (80% of usage)
const PRIORITY_NODES = {
  'nodes-base.httpRequest': {
    required: ['url'],
    common: ['method', 'authentication', 'sendBody', 'contentType', 'sendHeaders']
  },
  'nodes-base.webhook': {
    required: [],
    common: ['httpMethod', 'path', 'responseMode', 'responseData']
  },
  'nodes-base.code': {
    required: [],
    common: ['language', 'jsCode', 'pythonCode']
  },
  'nodes-base.set': {
    required: [],
    common: ['mode', 'assignments', 'options']
  },
  'nodes-base.if': {
    required: [],
    common: ['conditions', 'combineOperation']
  },
  'nodes-base.postgres': {
    required: [],
    common: ['operation', 'table', 'query', 'additionalFields']
  },
  'nodes-base.openAi': {
    required: [],
    common: ['resource', 'operation', 'modelId', 'prompt', 'messages']
  },
  'nodes-base.googleSheets': {
    required: [],
    common: ['operation', 'sheetId', 'range', 'dataStartRow']
  },
  'nodes-base.slack': {
    required: [],
    common: ['resource', 'operation', 'channel', 'text', 'attachments']
  },
  'nodes-base.email': {
    required: [],
    common: ['fromEmail', 'toEmail', 'subject', 'text', 'html']
  }
};

Success Criteria

Week 1

• get_node_essentials working for 20 nodes
• 90%+ size reduction achieved
• Examples provided for common use cases
• Property search implemented

Week 2

• Configuration validation working
• 10+ task templates created
• Error messages are helpful
• AI agents successfully creating workflows

Month 1

• 50+ nodes optimized
• Advanced features implemented
• Documentation updated
• Migration guide created

Quick Test Commands

# Test essentials tool
echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"get_node_essentials","arguments":{"nodeType":"nodes-base.httpRequest"}},"id":1}' | npm start

# Compare with original
echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"get_node_info","arguments":{"nodeType":"nodes-base.httpRequest"}},"id":1}' | npm start

# Test property search
echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"search_node_properties","arguments":{"nodeType":"nodes-base.httpRequest","query":"auth"}},"id":1}' | npm start

Remember

1. Start small - Get one tool working perfectly before moving on
2. Test with real AI - Use Claude/GPT to validate improvements
3. Iterate quickly - Refine based on what works
4. Keep compatibility - Don't break existing tools
5. Measure everything - Track size reduction and success rates

Next Steps

1. Review this plan with your team
2. Start with Day 1 implementation
3. Test with HTTP Request node
4. Get feedback from AI agents
5. Iterate and improve

The key is to deliver value incrementally while building toward the complete solution.