Quantitative Strategy MCP

A professional MCP (Model Context Protocol) skill package for quantitative trading strategy research and backtesting.

Features

• 📊 Data Access: Get stock historical data and stock lists
• 🧮 Factor Calculation: Calculate technical indicators (RSI, MACD, Momentum, etc.)
• 🧪 Backtesting: Run strategy backtests with realistic assumptions
• 📈 Strategy Evaluation: Multi-dimensional strategy performance evaluation
• 🔔 Real-time Monitoring: Stock price monitoring with alerts

Installation

1. Clone the repository

2. Install dependencies:

   pip install numpy pandas

3. Configure database path in config/config.py

Usage

As MCP Skill

Add to your MCP server configuration:

{
  "mcpServers": {
    "quantitative-strategy": {
      "command": "python",
      "args": ["src/mcp_tools.py"],
      "cwd": "/path/to/quantitative_strategy_mcp",
      "env": {
        "DB_PATH": "/path/to/your/database.db"
      }
    }
  }
}

As Python Library

from src.mcp_tools import call_mcp_tool

# Get stock data
result = call_mcp_tool(
    'get_stock_data',
    ts_code='000001.SZ',
    start_date='20240101',
    end_date='20241231'
)

# Calculate factor
factor = call_mcp_tool(
    'calculate_factor',
    data=result['data'],
    factor_type='rsi',
    params={'period': 14}
)

# Run backtest
backtest = call_mcp_tool(
    'run_backtest',
    ts_code='000001.SZ',
    start_date='20240101',
    end_date='20241231',
    strategy_type='momentum'
)

Available Tools

1. get_stock_data - Get stock historical data
2. get_stock_list - Get stock list
3. calculate_factor - Calculate quantitative factors
4. run_backtest - Run strategy backtest
5. evaluate_strategy - Evaluate strategy performance
6. monitor_stocks - Monitor stock prices

Documentation

See docs/QUANT_MCP_SKILL.md for detailed documentation.

Examples

Check examples/ directory for usage examples.

License

MIT License

Author

马上有钱 (Robot)

Version

1.0.0 (2026-03-15)

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🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

📄 License

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

🙏 Acknowledgments

• Built with inspiration from ClawHub FinStep MCP
• Thanks to the quantitative trading community

📬 Contact

• Issues: GitHub Issues
• Discussions: GitHub Discussions

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Made with ❤️ by 马上有钱 (Robot)