Xtquant AI

🚀 xtquantai

xtquantai is a server based on the Model Context Protocol (MCP). It integrates the functions of the Xuntou (xtquant) quantitative trading platform with an AI assistant, enabling the AI to directly access and operate quantitative trading data and functions.

🚀 Quick Start

XTQuantAI is a server that combines the capabilities of the Xuntou (xtquant) quantitative trading platform with an AI assistant, allowing the AI to directly access and manipulate quantitative trading data and functions.

✨ Features

XTQuantAI offers the following core features (continuously updated; feel free to submit new ideas):

Basic Data Query

• Get Trading Dates (get_trading_dates) - Retrieve trading dates for a specified market.
• Get Stock List by Sector (get_stock_list) - Obtain the list of stocks in a specific sector.
• Get Instrument Details (get_instrument_detail) - Fetch detailed information about a stock.

Market Data

• Get Historical Market Data (get_history_market_data) - Retrieve historical market data for a stock.
• Get Real-time Market Data (get_realtime_market_data) - Obtain real-time market data for a stock.
• Subscribe to Market Updates (subscribe_market_updates) - Subscribe to and receive real-time market updates.

Charting and Visualization

• Generate Price Chart (generate_price_chart) - Generate a price chart for a specified stock by providing a time range and parameters.
• Technical Indicator Analysis (technical_indicator_analysis) - Calculate and return technical indicators (e.g., moving averages, relative strength index) for a stock.

📦 Installation

Prerequisites

• Python 3.11 or higher
• Install QMT or the research and investment terminal
• Install the uv package management tool

Download and Installation

git clone https://github.com/your-repository/xtquantai.git
cd xtquantai
pip install -r requirements.txt

💻 Usage Examples

Integrating the MCP Server in Cursor (Windows only)

Method 1: Start via main.py

Run the following command in the project root directory:

python main.py

Method 2: Run Directly via Python Script

Execute the server_direct.py file:

python server_direct.py

Tool Usage Examples

Get Trading Dates

from xtquantai import get_trading_dates

dates = get_trading_dates(start_date="2023-01-01", end_date="2023-12-31")
print(dates)

Get Stock List by Sector

from xtquantai import get_stock_list_by_sector

sector_stocks = get_stock_list_by_sector(sector_id="Technology")
print(sector_stocks)

Generate Price Chart

from xtquantai import generate_price_chart

generate_price_chart(stock_code="AAPL", start_date="2023-01-01", end_date="2023-12-31", save_path="chart.png")

📚 Documentation

Start the Server

python src/xtquantai/server.py

Debugging with MCP Inspector (for development only)

After installing the Node.js environment, run the following command:

npx @modelcontextprotocol/inspector uv run xtquantai

Build and Publish

1. Synchronize dependencies and update the lock file:

   uv sync
   

2. Build the package distribution:

   uv build
   

3. Publish to PyPI:

   uv publish
   

Debugging

Debugging can be challenging since the MCP server runs through standard input/output. We highly recommend using MCP Inspector for debugging.

🔧 Technical Details

Project Structure

xtquantai/
├── src/
│   └── xtquantai/
│       ├── __init__.py    # Package initialization file
│       └── server.py      # MCP server implementation
├── main.py                # Startup script
├── server_direct.py       # Direct HTTP server implementation
├── pyproject.toml         # Project configuration
└── README.md              # Project documentation

📄 License

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

🤝 Contribution

Contributions are welcome! Please feel free to submit issues or pull requests.

🙏 Acknowledgments

• Xuntou Technology for providing the quantitative trading platform.
• Model Context Protocol for providing the AI integration framework.