name: mcp_server_developer
router_kit: FullStackKit
description: Model Context Protocol (MCP) server implementation specialist for Claude Desktop integration. Handles TypeScript/Node.js server scaffolding, endpoint creation, telemetry setup, npx distribution, and comprehensive documentation. Follows MCP specification and best practices for production-grade server deployment.
metadata:
skillport:
category: auto-healed
tags: [automation, aws, bash scripting, ci/cd, cloud computing, containerization, deployment strategies, devops, docker, gitops, infrastructure, infrastructure as code, integration, json-rpc, kubernetes, linux, logging, mcp server developer, microservices, monitoring, orchestration, pipelines, protocol, reliability, scalability, security, server, server management, terraform, tool-use]

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

2. MCP Server Setup

3. Install MCP SDK: npm install @modelcontextprotocol/sdk
4. Create server entry point (src/index.ts)
5. Implement stdio transport handler

6. Add basic resource/tool endpoints

7. Type Definitions
   ```typescript
   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
   ```sql
   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
);
```

1. Endpoint Implementation
2. GET resource endpoints (models list, transformations)
3. POST tool endpoints (analyze, decompose, synthesize)
4. Error handling with MCP-compliant responses

5. Input validation with Zod or similar

6. Transformation Logic

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

Phase 2: Documentation & Examples (Week 3)

1. Quick Start Guide (5-minute setup)
   ```markdown
   # Quick Start

2. Install via npx:
   bash npx @hummbl/mcp-server

3. Configure Claude Desktop:
   Add to claude_desktop_config.json:
   json { "mcpServers": { "hummbl": { "command": "npx", "args": ["@hummbl/mcp-server"] } } }

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

5. Runnable Examples

6. Example 1: Code analysis with decomposition
7. Example 2: Strategy synthesis with composition

8. Example 3: Decision making with perspective + inversion

9. Troubleshooting Guide

10. Installation failures (permissions, npm config)
11. Claude Desktop connection issues
12. Latency/performance problems
13. Error message reference

Phase 3: Distribution & Testing (Week 4)

1. NPX Setup
   json { "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

3. GitHub Actions for automated testing
4. Automated npm publishing on release tags
5. Cross-platform binary testing

6. Documentation deployment

7. Beta Testing

8. 3-5 beta testers minimum
9. Structured feedback collection
10. Performance benchmarking
11. 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
MCP Server Developer v1.1 - Enhanced

🔄 Workflow

Source: Anthropic MCP SDK Best Practices

Phase 1: Architecture & Setup

• [ ] Scaffolding: Run npm init and configure TypeScript settings.
• [ ] Types: Define Resource and Tool types with strict mode.
• [ ] Transport: Secure stdio transport with onerror handler.

Phase 2: Development Loop

• [ ] Hot Reload: Use nodemon or watch mode during development.
• [ ] Inspector: Live debug with npx @modelcontextprotocol/inspector.
• [ ] Logging: Add structured logging (JSON) but do not pollute stdio (use stderr).

Phase 3: Release

• [ ] Distribution: Publish package to npm or in a way that works with npx.
• [ ] Docs: Add claude_desktop_config.json example to README.md.
• [ ] Analytics: Set up anonymous usage data collection (opt-in) mechanism.

Checkpoints