MCP Server Developer

Expert implementation of Model Context Protocol (MCP) servers for Claude Desktop integration. This skill provides comprehensive guidance for building production-ready MCP servers with TypeScript, including architecture design, endpoint implementation, database integration, telemetry tracking, and distribution via npx.

Core Competencies

1. MCP Server Architecture

• Scaffold Generation: TypeScript project setup with proper MCP protocol structure
• Server Configuration: MCP protocol compliance, JSON-RPC handling, stdio transport
• Endpoint Design: RESTful-style resource and tool endpoints following MCP spec
• Type Safety: Strict TypeScript types for requests, responses, and schemas
• Error Handling: Comprehensive error catching with proper MCP error responses

2. Database Integration

• D1 SQLite Setup: Schema design optimized for edge deployment
• Query Optimization: <500ms latency targets for all database operations
• FTS5 Search: Full-text search implementation for model discovery
• Data Modeling: Efficient table structures with proper indexing
• Migration Scripts: Version-controlled schema evolution

3. Telemetry & Analytics

• Event Tracking: Structured logging for install, usage, and performance metrics
• Latency Monitoring: Request timing with percentile tracking (p50, p95, p99)
• User Analytics: Privacy-respecting usage patterns without PII
• Error Reporting: Structured error logging for debugging
• Success Metrics: WAU (Weekly Active Users) and engagement tracking

4. NPX Distribution

• Package Configuration: package.json with proper bin entries for npx execution
• Version Management: Semantic versioning with changelog automation
• Publishing Workflow: npm registry deployment with CI/CD integration
• Update Strategy: Non-breaking updates with deprecation notices
• Installation Testing: Cross-platform verification (macOS, Windows, Linux)

Implementation Guidelines

Phase 0: Server Scaffold (Week 1)

1. Initialize TypeScript Project

   npm init -y
   npm install --save-dev typescript @types/node
   npx tsc --init
   

2. MCP Server Setup

   • Install MCP SDK: npm install @modelcontextprotocol/sdk
   • Create server entry point (src/index.ts)
   • Implement stdio transport handler
   • Add basic resource/tool endpoints

3. Type Definitions

   interface MCPServer {
     name: string;
     version: string;
     resources: Resource[];
     tools: Tool[];
   }
   
   interface Resource {
     uri: string;
     name: string;
     description: string;
     mimeType?: string;
   }
   
   interface Tool {
     name: string;
     description: string;
     inputSchema: JSONSchema;
   }
   

Phase 1: Core Functionality (Week 2)

1. Database Schema

   CREATE TABLE mental_models (
     id TEXT PRIMARY KEY,
     code TEXT UNIQUE NOT NULL,
     transformation_class TEXT NOT NULL,
     name TEXT NOT NULL,
     description TEXT,
     use_cases JSON,
     difficulty_tier INTEGER,
     prerequisites JSON,
     created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
   );
   
   CREATE VIRTUAL TABLE models_fts USING fts5(
     code, name, description, use_cases
   );
   

2. Endpoint Implementation

   • GET resource endpoints (models list, transformations)
   • POST tool endpoints (analyze, decompose, synthesize)
   • Error handling with MCP-compliant responses
   • Input validation with Zod or similar

3. Transformation Logic

   • Perspective (P): Multi-viewpoint analysis
   • Inversion (IN): Reverse assumption mapping
   • Composition (CO): Integration synthesis
   • Decomposition (DE): Component breakdown
   • Recursion (RE): Feedback loop identification
   • Meta-Systems (SY): Systems-of-systems coordination

Phase 2: Documentation & Examples (Week 3)

1. Quick Start Guide (5-minute setup)

   # Quick Start
   
   1. Install via npx:
      ```bash
      npx @hummbl/mcp-server
   

   2. Configure Claude Desktop: Add to claude_desktop_config.json:

      {
        "mcpServers": {
          "hummbl": {
            "command": "npx",
            "args": ["@hummbl/mcp-server"]
          }
        }
      }
      

   3. Test in Claude: "Use the perspective transformation on this problem: [your problem]"

2. Runnable Examples

   • Example 1: Code analysis with decomposition
   • Example 2: Strategy synthesis with composition
   • Example 3: Decision making with perspective + inversion

3. Troubleshooting Guide

   • Installation failures (permissions, npm config)
   • Claude Desktop connection issues
   • Latency/performance problems
   • Error message reference

Phase 3: Distribution & Testing (Week 4)

1. NPX Setup

   {
     "name": "@hummbl/mcp-server",
     "version": "1.0.0",
     "bin": {
       "hummbl-mcp": "./dist/index.js"
     },
     "files": ["dist", "README.md", "LICENSE"],
     "publishConfig": {
       "access": "public"
     }
   }
   

2. CI/CD Pipeline

   • GitHub Actions for automated testing
   • Automated npm publishing on release tags
   • Cross-platform binary testing
   • Documentation deployment

3. Beta Testing

   • 3-5 beta testers minimum
   • Structured feedback collection
   • Performance benchmarking
   • Edge case identification

Quality Gates

Functional Requirements ✅

• All MCP endpoints respond correctly to spec
• Database queries complete <500ms (p95)
• Zero crashes during 24-hour stability test
• Error handling covers all edge cases
• Type safety: 100% TypeScript strict mode

Documentation Requirements ✅

• Quick start achieves first run in <5 minutes
• All examples run without modification
• Troubleshooting covers 90%+ of common issues
• API reference is complete and accurate
• Inline code comments for complex logic

Adoption Requirements ✅

• 10+ Weekly Active Users (WAU) by target date
• 3+ beta testers provide positive feedback
• Zero P0 bugs in production after Week 2
• Average user rating ≥4.0/5.0
• MCP directory listing approved

MCP Protocol Compliance

Required Capabilities

1. Resources: Read-only data access (models, transformations)
2. Tools: Interactive operations (analyze, decompose, synthesize)
3. Prompts: Pre-defined workflows (optional in Phase 0)

Transport Layer

• stdio: Standard input/output for Claude Desktop
• JSON-RPC 2.0: All requests/responses follow spec
• Error Codes: Proper HTTP-style error codes

Security Best Practices

• Input sanitization for all user-provided data
• Rate limiting to prevent abuse
• No external network calls without explicit permission
• Minimal permissions model
• Audit logging for all operations

Performance Optimization

Latency Targets

• p50: <100ms for all endpoints
• p95: <500ms for database queries
• p99: <1000ms for complex transformations

Optimization Strategies

1. Database: Index all frequently queried columns
2. Caching: In-memory LRU cache for hot data
3. Lazy Loading: Load resources only when needed
4. Batch Operations: Group similar queries
5. Connection Pooling: Reuse database connections

Telemetry Schema

interface TelemetryEvent {
  event_name: 'mcp_install' | 'mcp_success_run' | 'api_call' | 'doc_view';
  user_id: string; // Anonymized hash
  ts: string; // ISO 8601
  meta: {
    client?: string; // Claude Desktop version
    version?: string; // MCP server version
    model?: string; // e.g., "CO4"
    lat_ms?: number; // Latency in milliseconds
    endpoint?: string; // Endpoint called
    status?: number; // HTTP-style status code
  };
}

Distribution Checklist

Pre-Publication ✅

• Version number updated (semantic versioning)
• CHANGELOG.md updated with release notes
• README.md reviewed and accurate
• LICENSE file present (MIT recommended)
• package.json metadata complete
• Dependencies audit clean (npm audit)
• Bundle size acceptable (<5MB)

MCP Directory Submission ✅

• Clear description (160 characters max)
• Category selection appropriate
• Screenshots/demos prepared
• Usage examples documented
• Support contact provided

Post-Publication ✅

• NPM package downloadable via npx
• GitHub release created with notes
• Documentation site updated
• Community announcement posted
• Beta testers notified

Common Pitfalls & Solutions

Issue: Claude Desktop doesn't detect server

Solution: Verify stdio transport is properly initialized and JSON-RPC responses are formatted correctly.

Issue: High latency (>1s)

Solution: Add database indexes, implement caching, or optimize query complexity.

Issue: Installation fails on Windows

Solution: Test with cross-platform paths, avoid shell-specific commands, use cross-env for environment variables.

Issue: Breaking changes between versions

Solution: Follow semantic versioning strictly, maintain backwards compatibility, provide migration guides.

Examples

Example 1: Minimal MCP Server

import { Server } from '@modelcontextprotocol/sdk/server/index.js';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';

const server = new Server({
  name: 'hummbl-mcp-server',
  version: '1.0.0',
}, {
  capabilities: {
    resources: {},
    tools: {},
  },
});

// Register resource: List mental models
server.setRequestHandler('resources/list', async () => ({
  resources: [
    {
      uri: 'hummbl://models',
      name: 'Mental Models',
      description: 'BASE120 mental model collection',
      mimeType: 'application/json',
    },
  ],
}));

// Register tool: Analyze with perspective transformation
server.setRequestHandler('tools/call', async (request) => {
  if (request.params.name === 'analyze-perspective') {
    const { text } = request.params.arguments;
    // Transformation logic here
    return {
      content: [{
        type: 'text',
        text: `Perspective analysis: ${text}`,
      }],
    };
  }
});

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Example 2: Database Integration

import Database from 'better-sqlite3';

const db = new Database('hummbl.db');

// Initialize schema
db.exec(`
  CREATE TABLE IF NOT EXISTS mental_models (
    id TEXT PRIMARY KEY,
    code TEXT UNIQUE NOT NULL,
    transformation_class TEXT NOT NULL,
    name TEXT NOT NULL,
    description TEXT
  );
  
  CREATE INDEX IF NOT EXISTS idx_transformation 
  ON mental_models(transformation_class);
`);

// Query with prepared statement
const getModelsByTransformation = db.prepare(`
  SELECT * FROM mental_models 
  WHERE transformation_class = ? 
  ORDER BY code
`);

const perspectiveModels = getModelsByTransformation.all('P');

Example 3: Telemetry Logging

function logTelemetry(event: TelemetryEvent) {
  const logEntry = {
    ...event,
    ts: new Date().toISOString(),
  };
  
  // Log to console (development)
  if (process.env.NODE_ENV === 'development') {
    console.log(JSON.stringify(logEntry));
  }
  
  // Send to analytics service (production)
  if (process.env.NODE_ENV === 'production') {
    // TODO: Send to analytics endpoint
  }
}

// Usage
logTelemetry({
  event_name: 'api_call',
  user_id: hashUserId(userId),
  ts: new Date().toISOString(),
  meta: {
    endpoint: '/tools/analyze-perspective',
    lat_ms: 245,
    status: 200,
  },
});

Resources

• MCP Specification: https://spec.modelcontextprotocol.io/
• MCP SDK: https://github.com/modelcontextprotocol/typescript-sdk
• Claude Desktop Config: https://docs.claude.com/en/docs/agents-and-tools/agent-skills
• TypeScript Best Practices: https://typescript-lang.org/docs/handbook/intro.html
• NPM Publishing Guide: https://docs.npmjs.com/packages-and-modules/contributing-packages-to-the-registry

Success Criteria

Phase 0 is successful when:

1. ✅ npx @hummbl/mcp-server runs cleanly on any machine
2. ✅ 10+ developers using it weekly by target date
3. ✅ 3 compelling examples work out-of-the-box
4. ✅ Zero P0 bugs after Week 2
5. ✅ Clear path to Phase 1 identified

Phase 0 fails if:

1. ❌ <10 users after 60 days → Pivot to consulting focus
2. ❌ >5 P0 bugs in first 30 days → Architecture review needed
3. ❌ >1000ms latency sustained → Tech stack reassessment required