TAM-MCP-Server

A comprehensive Model Context Protocol (MCP) server for market sizing analysis, TAM/SAM calculations, and industry research. Built with TypeScript, Express.js, and following the MCP 2024-11-05 specification.

🚀 Features

Core Capabilities

• 10 Specialized Market Analysis Tools for comprehensive market research
• HTTP Streamable Transport with Server-Sent Events for real-time updates
• Advanced Caching System with configurable TTL and performance optimization
• Comprehensive Logging with structured Winston logging and business metrics
• Prometheus Metrics for monitoring and observability
• Enterprise Security with rate limiting, CORS, and input validation
• Session Management for stateful interactions

Market Analysis Tools

1. 🔍 Industry Search - Find and explore industry sectors and categories
2. 📊 Industry Data - Get detailed industry statistics and metrics
3. 📈 Market Size - Calculate current market size with multiple methodologies
4. 🎯 TAM Calculator - Total Addressable Market analysis and calculations
5. 🎪 SAM Calculator - Serviceable Addressable Market segmentation
6. 🧩 Market Segments - Detailed market segmentation analysis
7. 📊 Market Forecasting - Future market projections and trend analysis
8. ⚖️ Market Comparison - Compare multiple markets and industries
9. ✅ Data Validation - Validate and verify market data accuracy
10. 💡 Market Opportunities - Identify growth opportunities and market gaps

🛠 Installation

Prerequisites

• Node.js 18+
• npm or yarn
• TypeScript 5+

Quick Start

# Clone the repository
git clone https://github.com/gvaibhav/TAM-MCP-Server.git
cd TAM-MCP-Server

# Install dependencies
npm install

# Copy environment configuration
cp .env.example .env

# Edit configuration (add your API keys)
nano .env

# Start development server
npm run dev

# Or build and run production
npm run build
npm start

Docker Installation

# Build Docker image
docker build -t tam-mcp-server .

# Run with Docker Compose
docker-compose up -d

# Or run standalone
docker run -p 3000:3000 -e NODE_ENV=production tam-mcp-server

📋 Configuration

Environment Variables

Variable	Description	Default	Required
PORT	Server port	3000	No
HOST	Server host	0.0.0.0	No
NODE_ENV	Environment	development	No
CORS_ORIGIN	CORS origin	*	No
RATE_LIMIT_MAX	Rate limit per window	100	No
CACHE_TTL	Cache TTL (seconds)	300	No
SESSION_SECRET	Session secret key	-	Yes
MARKET_DATA_API_KEY	Market data provider API key	-	Recommended
LOG_LEVEL	Logging level	info	No

API Keys Configuration

The server supports multiple market data providers:

• IBISWorld - Industry reports and analysis
• Statista - Market statistics and data
• Grand View Research - Market research reports
• Bloomberg - Financial and market data
• PitchBook - Private market data

Add your API keys to the .env file to enable real data integration.

🚦 API Endpoints

MCP Protocol Endpoints

• GET /mcp/discovery - Server capabilities and tool discovery
• POST /mcp/session - Create and manage MCP sessions
• POST /mcp/tools/{tool_name} - Execute specific market analysis tools
• GET /mcp/events - Server-Sent Events stream for real-time updates
• GET /mcp/health - Health check and server status
• GET /mcp/metrics - Prometheus metrics endpoint

Tool Execution Examples

# Search for industries
curl -X POST http://localhost:3000/mcp/tools/industry_search \
  -H "Content-Type: application/json" \
  -d '{"query": "artificial intelligence", "filters": {"region": "global"}}'

# Calculate TAM
curl -X POST http://localhost:3000/mcp/tools/calculate_tam \
  -H "Content-Type: application/json" \
  -d '{"industry": "SaaS", "geography": "North America", "timeframe": "2024"}'

# Get market forecast
curl -X POST http://localhost:3000/mcp/tools/forecast_market \
  -H "Content-Type: application/json" \
  -d '{"industry": "Cloud Computing", "years": 5, "methodology": "compound_growth"}'

🏗 Architecture

Project Structure

src/
├── index.ts              # Main entry point
├── server.ts             # Express server setup
├── types/
│   └── schemas.ts        # Zod schemas and TypeScript types
├── tools/
│   └── mcpTools.ts       # MCP tool implementations
├── services/
│   ├── dataService.ts    # Data operations and API integrations
│   └── cacheService.ts   # Caching service with NodeCache
└── utils/
    └── logger.ts         # Winston logging utility

Technology Stack

• Runtime: Node.js 18+ with ES modules
• Framework: Express.js with TypeScript
• Validation: Zod for runtime type safety
• Caching: NodeCache with TTL support
• Logging: Winston with structured logging
• Metrics: Prometheus client for monitoring
• Security: Helmet, CORS, rate limiting
• Transport: HTTP with Server-Sent Events

🧪 Testing

# Run all tests
npm test

# Run tests with coverage
npm run test:coverage

# Run specific test suite
npm test -- --grep "MCPTools"

# Run integration tests
npm run test:integration

Test Structure

• Unit Tests - Individual component testing
• Integration Tests - API endpoint testing
• Performance Tests - Load and stress testing
• Security Tests - Vulnerability scanning

📊 Monitoring & Observability

Prometheus Metrics

The server exposes comprehensive metrics at /mcp/metrics:

• Request Metrics - Request count, duration, status codes
• Tool Metrics - Tool execution time and success rates
• Cache Metrics - Hit/miss ratios and performance
• Business Metrics - Market analysis usage patterns
• System Metrics - Memory, CPU, and resource usage

Logging

Structured JSON logging with multiple levels:

// Business metrics logging
logger.business('market_analysis_completed', {
  tool: 'calculate_tam',
  industry: 'SaaS',
  result_size: 1234567890,
  execution_time: 1250
});

// Performance profiling
logger.profile('api_request', requestId);
// ... operation ...
logger.profile('api_request', requestId); // Logs duration

🔒 Security

Security Features

• Rate Limiting - Configurable per-IP request limits
• Input Validation - Zod schema validation for all inputs
• CORS Protection - Configurable cross-origin policies
• Security Headers - Helmet.js security headers
• Session Management - Secure session handling
• API Key Management - Secure API key storage and rotation

Production Security Checklist

• Change default SESSION_SECRET
• Configure specific CORS_ORIGIN
• Set up HTTPS/TLS certificates
• Configure firewall rules
• Enable security monitoring
• Set up log aggregation
• Configure backup and recovery

🚀 Deployment

Docker Deployment

# docker-compose.yml
version: '3.8'
services:
  market-sizing-mcp:
    build: .
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - SESSION_SECRET=your-secure-secret
    volumes:
      - ./logs:/app/logs
    restart: unless-stopped

Kubernetes Deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  name: market-sizing-mcp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: market-sizing-mcp
  template:
    metadata:
      labels:
        app: market-sizing-mcp
    spec:
      containers:
      - name: market-sizing-mcp
        image: market-sizing-mcp:latest
        ports:
        - containerPort: 3000
        env:
        - name: NODE_ENV
          value: "production"

Cloud Deployment

• AWS: ECS, Lambda, or EC2 with Application Load Balancer
• Google Cloud: Cloud Run, GKE, or Compute Engine
• Azure: Container Instances, AKS, or App Service
• Heroku: Direct deployment with buildpack

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Workflow

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes with tests
4. Run linting: npm run lint:fix
5. Run tests: npm test
6. Commit with conventional commits: git commit -m "feat: add amazing feature"
7. Push and create a Pull Request

Code Standards

• TypeScript with strict mode enabled
• ESLint for code linting
• Prettier for code formatting
• Conventional Commits for commit messages
• 100% test coverage for new features

📝 Changelog

See CHANGELOG.md for version history and release notes.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Documentation: GitHub Wiki
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Author: @gvaibhav

🙏 Acknowledgments

• Model Context Protocol specification by Anthropic
• Market Research Community for methodology guidance
• Open Source Contributors who made this project possible

---

Created by Gvaibhav with ❤️ for the market research and business intelligence community