- Add get_node_essentials tool for 10-20 essential properties only - Add search_node_properties for targeted property search - Add get_node_for_task with 14 pre-configured templates - Add validate_node_config for comprehensive validation - Add get_property_dependencies for visibility analysis - Implement PropertyFilter service with curated essentials - Implement ExampleGenerator with working examples - Implement TaskTemplates for common workflows - Implement ConfigValidator with security checks - Implement PropertyDependencies for dependency analysis - Enhance property descriptions to 100% coverage - Add version information to essentials response - Update documentation with new tools Response sizes reduced from 100KB+ to <5KB for better AI agent usability. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
198 lines
5.4 KiB
Markdown
198 lines
5.4 KiB
Markdown
# MCP Implementation Action Plan
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## Key Insights from Analysis
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### ✅ What You Already Have (Working Well)
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1. **Excellent property extraction** - All properties with complete schemas
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2. **Proper data structure** - Properties include types, options, displayOptions
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3. **Efficient storage** - JSON in SQLite is perfect for this use case
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4. **Complete metadata** - Operations, credentials, documentation all captured
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### ❌ The Real Problem
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- **Information overload**: Returning 200+ properties when AI needs 10-20
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- **No filtering**: All properties returned regardless of relevance
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- **Poor organization**: Essential mixed with advanced properties
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- **No examples**: AI agents need concrete examples to work from
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### 💡 The Solution
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**Don't restructure - add intelligent filtering layers on top**
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## Immediate Action Plan (This Week)
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### Day 1-2: Implement get_node_essentials
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1. **Create services**:
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```bash
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touch src/services/property-filter.ts
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touch src/services/example-generator.ts
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```
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2. **Copy code from implementation guide**:
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- PropertyFilter class with essential lists
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- ExampleGenerator with concrete examples
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- Tool implementation in server.ts
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3. **Test with top 5 nodes**:
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- nodes-base.httpRequest
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- nodes-base.webhook
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- nodes-base.code
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- nodes-base.set
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- nodes-base.postgres
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4. **Measure improvement**:
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```bash
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npm run build
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node scripts/test-essentials.js
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```
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### Day 3: Expand Coverage
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1. **Add 15 more nodes** to ESSENTIAL_PROPERTIES:
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- nodes-base.if
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- nodes-base.merge
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- nodes-base.splitInBatches
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- nodes-base.function
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- nodes-base.email
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- nodes-base.slack
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- nodes-base.github
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- nodes-base.googleSheets
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- nodes-base.openAi
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- nodes-base.redis
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- nodes-base.mongodb
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- nodes-base.mysql
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- nodes-base.ftp
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- nodes-base.ssh
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- nodes-base.executeCommand
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2. **Create examples** for each node
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3. **Test with AI agents**
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### Day 4-5: Implement search_node_properties
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1. **Create property flattener**:
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```typescript
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// Converts nested properties to flat list with paths
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class PropertyFlattener {
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static flatten(properties: any[], path = ''): FlatProperty[]
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}
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```
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2. **Add search functionality**:
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- Search by name
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- Search by description
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- Search by type
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3. **Test search accuracy**
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### Week 2: Validation & Task Templates
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1. **Implement validate_node_config**:
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- Check required properties
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- Validate against displayOptions
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- Provide helpful error messages
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2. **Create task templates**:
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- Common API patterns
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- Database operations
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- File handling
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- Webhook patterns
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## Essential Property Lists (Starting Point)
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```typescript
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// Top 20 nodes to optimize first (80% of usage)
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const PRIORITY_NODES = {
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'nodes-base.httpRequest': {
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required: ['url'],
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common: ['method', 'authentication', 'sendBody', 'contentType', 'sendHeaders']
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},
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'nodes-base.webhook': {
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required: [],
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common: ['httpMethod', 'path', 'responseMode', 'responseData']
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},
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'nodes-base.code': {
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required: [],
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common: ['language', 'jsCode', 'pythonCode']
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},
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'nodes-base.set': {
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required: [],
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common: ['mode', 'assignments', 'options']
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},
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'nodes-base.if': {
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required: [],
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common: ['conditions', 'combineOperation']
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},
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'nodes-base.postgres': {
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required: [],
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common: ['operation', 'table', 'query', 'additionalFields']
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},
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'nodes-base.openAi': {
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required: [],
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common: ['resource', 'operation', 'modelId', 'prompt', 'messages']
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},
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'nodes-base.googleSheets': {
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required: [],
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common: ['operation', 'sheetId', 'range', 'dataStartRow']
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},
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'nodes-base.slack': {
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required: [],
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common: ['resource', 'operation', 'channel', 'text', 'attachments']
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},
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'nodes-base.email': {
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required: [],
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common: ['fromEmail', 'toEmail', 'subject', 'text', 'html']
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}
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};
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```
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## Success Criteria
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### Week 1
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- [ ] get_node_essentials working for 20 nodes
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- [ ] 90%+ size reduction achieved
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- [ ] Examples provided for common use cases
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- [ ] Property search implemented
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### Week 2
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- [ ] Configuration validation working
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- [ ] 10+ task templates created
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- [ ] Error messages are helpful
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- [ ] AI agents successfully creating workflows
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### Month 1
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- [ ] 50+ nodes optimized
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- [ ] Advanced features implemented
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- [ ] Documentation updated
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- [ ] Migration guide created
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## Quick Test Commands
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```bash
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# Test essentials tool
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echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"get_node_essentials","arguments":{"nodeType":"nodes-base.httpRequest"}},"id":1}' | npm start
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# Compare with original
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echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"get_node_info","arguments":{"nodeType":"nodes-base.httpRequest"}},"id":1}' | npm start
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# Test property search
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echo '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"search_node_properties","arguments":{"nodeType":"nodes-base.httpRequest","query":"auth"}},"id":1}' | npm start
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```
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## Remember
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1. **Start small** - Get one tool working perfectly before moving on
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2. **Test with real AI** - Use Claude/GPT to validate improvements
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3. **Iterate quickly** - Refine based on what works
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4. **Keep compatibility** - Don't break existing tools
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5. **Measure everything** - Track size reduction and success rates
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## Next Steps
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1. Review this plan with your team
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2. Start with Day 1 implementation
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3. Test with HTTP Request node
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4. Get feedback from AI agents
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5. Iterate and improve
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The key is to **deliver value incrementally** while building toward the complete solution. |