What dependencies does FinQ4Cn MCP Server require?
It requires FastMCP, Pydantic, and akshare. For backtesting, it also depends on the `lib‑pybroker` package.
@jinhongzou
基本信息
适合国内使用的量化金融mcp server
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"FinQ4Cn-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
FinQ4Cn MCP Server is a specialized MCP server tool for quantitative analysis that provides large language models with free, open-source access to Chinese A‑share financial data. Built on the akshare library, it offers comprehensive data on stocks, financial indicators, and market volatility, targeting professionals in quantitative analysis and investors interested in China’s domestic stock market.
Clone the repository, create a Python virtual environment, install dependencies via pip install -r requirements.txt, and optionally pip install lib-pybroker for backtesting. Then configure your MCP client (e.g., Cherry Studio or MCP inspector) with the path to fs_server.py. Detailed JSON configuration for Cherry Studio is provided in the README.
It requires FastMCP, Pydantic, and akshare. For backtesting, it also depends on the `lib‑pybroker` package.
Yes, it is open source under the MIT License and provides free access to financial data via the akshare library.
It focuses on China’s A‑share market, including stock prices, financial summaries, margin trading, dividends, news, and backtesting capabilities. Future plans include funds, futures, and technical analysis.
Configure your MCP client (e.g., Cherry Studio or MCP inspector) to launch `fs_server.py` with your Python interpreter. Example JSON is provided in the README.
Yes, it provides a `strategy_buy_with_stop_loss` tool that backtests historical data using a buy‑and‑hold with profit‑taking strategy.
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