KaayaanAi/mcp-global-intelligence

MCP Global Intelligence

Advanced cryptocurrency market analysis server implementing the Model Context Protocol (MCP) with real-time data processing, technical analysis, and automated alerting capabilities.

Features

• Comprehensive Market Analysis: Technical indicators (RSI, Bollinger Bands, Moving Averages), sentiment analysis, and market predictions
• Real-time Data Processing: Live cryptocurrency price feeds with intelligent caching
• Automated Alert System: Smart notifications based on market conditions and risk thresholds
• Multi-Database Architecture: Redis caching, MongoDB analytics storage, PostgreSQL workflow logging
• WhatsApp Integration: Real-time notifications via WAHA API
• Portfolio Risk Assessment: Multi-asset risk analysis and diversification recommendations
• MCP 2025 Protocol: Latest Model Context Protocol implementation with WebSocket and SSE support

Quick Start

Prerequisites

• Python 3.11+
• Docker & Docker Compose
• Redis, MongoDB, PostgreSQL (or use Docker setup)

Installation

1. Clone and Setup Environment

   git clone <your-repo-url>
   cd mcp-global-intelligence
   cp .env.example .env
   

2. Configure Environment Variables

   Edit .env with your actual values:

   # Database connections
   REDIS_URL=redis://:password@host:6379/0
   MONGODB_URL=mongodb://user:pass@host:27017/database
   POSTGRES_URL=postgresql://user:pass@host:5432/database
   
   # WhatsApp alerts
   WHATSAPP_BASE_URL=https://your-waha-server.com
   WHATSAPP_SESSION=your_session_id
   ALERT_CHAT_ID=your_chat_id@c.us
   
   # API keys (optional but recommended)
   COINGECKO_API_KEY=your_coingecko_pro_key
   BINANCE_API_KEY=your_binance_key
   BINANCE_SECRET_KEY=your_binance_secret
   

3. Deploy with Docker

   # Quick start with Docker Compose
   docker compose up -d
   
   # Check logs
   docker logs -f mcp-global-intelligence
   

4. Manual Installation

   # Install dependencies
   pip install -r requirements.txt
   
   # Start server
   python main.py
   

MCP Tools Available

comprehensive_crypto_analysis

Complete cryptocurrency market analysis with technical indicators and predictions.

Parameters:

• symbol: Cryptocurrency symbol (e.g., "bitcoin", "ethereum")
• workflow_id: Optional workflow identifier for tracking

Returns: Technical analysis, sentiment data, risk assessment, price predictions, and automated alerts.

market_alerts_summary

Get recent market alerts and activity summary.

Parameters:

• hours: Time range for alert summary (default: 24)

Returns: Alert statistics, top active symbols, risk distribution, and market trends.

portfolio_risk_assessment

Analyze risk across multiple cryptocurrency holdings.

Parameters:

• symbols: Array of cryptocurrency symbols to analyze

Returns: Portfolio diversification analysis, risk metrics, correlation data, and rebalancing recommendations.

Architecture

Core Components

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Data Sources  │────│ Analysis Engine │────│ Alert System    │
│                 │    │                 │    │                 │
│ • CoinGecko API │    │ • Technical     │    │ • WhatsApp      │
│ • Binance API   │    │ • Sentiment     │    │ • Risk Alerts   │
│ • Fear/Greed    │    │ • Prediction    │    │ • Notifications │
└─────────────────┘    └─────────────────┘    └─────────────────┘
        │                       │                       │
        └───────────────────────┼───────────────────────┘
                                │
                    ┌─────────────────┐
                    │  Infrastructure │
                    │                 │
                    │ • Redis Cache   │
                    │ • MongoDB Store │
                    │ • PostgreSQL    │
                    └─────────────────┘

Project Structure

mcp-global-intelligence/
├── core/                   # Core business logic
│   ├── crypto_engine.py   # Market analysis engine
│   ├── kaayaan_integration.py # Infrastructure integration
│   └── mcp_server.py      # MCP protocol implementation
├── handlers/              # Request handlers
│   ├── analysis_handler.py
│   ├── alert_handler.py
│   └── portfolio_handler.py
├── utils/                 # Helper utilities
│   ├── calculations.py
│   ├── data_models.py
│   └── validators.py
├── config/               # Configuration management
│   └── settings.py
├── scripts/              # Deployment scripts
├── docs/                 # Documentation
├── tests/                # Test suite
├── docker-compose.yml    # Docker configuration
├── requirements.txt      # Python dependencies
└── main.py              # Application entry point

Configuration

Required Environment Variables

Optional Configuration

Usage Examples

MCP Client Integration

import json
from mcp import ClientSession

# Connect to MCP server
session = ClientSession("stdio", ["python", "main.py"])

# Analyze cryptocurrency
analysis = await session.call_tool("comprehensive_crypto_analysis", {
    "symbol": "bitcoin"
})

print(json.dumps(analysis.content, indent=2))

n8n Integration

1. Add MCP Client node to your workflow
2. Configure stdio connection: python main.py
3. Use available tools in automation workflows

See docs/n8n_integration_guide_comprehensive.md for detailed setup instructions.

Development

Local Development Setup

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/macOS
# or
venv\Scripts\activate     # Windows

# Install dependencies
pip install -r requirements.txt

# Run tests
python -m pytest tests/

# Start development server
python main.py

Running Tests

# Test infrastructure connections
python test_infrastructure.py

# Test core functionality
python test_core_infrastructure.py

# Run pytest suite
pytest tests/ -v

Deployment

Docker Deployment (Recommended)

# Build and deploy
docker compose up -d

# Scale for high availability
docker compose up -d --scale mcp-server=3

Manual Deployment

# Install system dependencies
sudo apt-get update
sudo apt-get install python3.11 python3-pip redis-server

# Deploy application
./scripts/production-startup.sh

Monitoring and Health Checks

Health Endpoints

The server includes built-in health monitoring:

# Check service health
curl http://localhost:8080/health

# Check infrastructure connections  
curl http://localhost:8080/health/infrastructure

Logging

Logs are structured in JSON format for production monitoring:

# View application logs
docker logs mcp-global-intelligence

# Follow logs in real-time
docker logs -f mcp-global-intelligence

Security

Security Features

• Environment-based Configuration: No hardcoded credentials
• Input Validation: All inputs sanitized and validated
• Rate Limiting: Protection against API abuse
• Secure Defaults: Production-hardened configuration
• Container Isolation: Docker-based deployment

Security Checklist

• All credentials in environment variables
• .env file not committed to version control
• Rate limiting configured for all APIs
• Container runs as non-root user
• Network access properly restricted
• Logs don't contain sensitive information

Troubleshooting

Common Issues

Connection Errors:

# Test database connections
python -c "from core.kaayaan_integration import KayaanIntegration; \
import asyncio; \
asyncio.run(KayaanIntegration().test_connections())"

Performance Issues:

# Check Redis memory usage
redis-cli info memory

# Monitor MongoDB operations
mongotop

# Check PostgreSQL connections
psql -h host -U user -c "SELECT * FROM pg_stat_activity;"

WhatsApp Integration Issues:

• Verify WAHA server is running and accessible
• Check session ID is valid and active
• Ensure chat ID format is correct (number@c.us)

Support

For issues and questions:

• Check the logs: docker logs mcp-global-intelligence
• Review configuration: Ensure all required environment variables are set
• Test infrastructure: Run python test_infrastructure.py

License

MIT License - See LICENSE file for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Submit a pull request

Ensure all tests pass and follow the existing code style before submitting.