Stock Analysis MCP Server

Stock Analysis MCP Server

A FastMCP-based server that provides tools for analyzing stock market data, including concept sector strength, financial indicators, F10 information, market emotion indicators, and tracking limit-up stocks.

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README

Stock Analysis MCP Server

This project is a server built using the FastMCP framework, providing various tools for accessing and analyzing stock market data.

Features

The server exposes the following tools:

  • Concept Power Tools (/stock): Analyzes the strength of stock concept sectors based on fund flow and price change.
  • Finance Tools (/finance): Provides access to stock financial core indicators and company information.
  • Stock F10 Tools (/f10): Fetches and summarizes Stock F10 information.
  • Market Emotion Tools (/market): Retrieves and summarizes A-share market emotion indicators.
  • Stock Keep Up Tools (/stockUp): Provides lists of continuous limit-up stocks and limit-up stocks.
  • Web Search Tools (Tavily) (/websearch): Provides a web search tool.

Setup and Installation

  1. Clone the repository:

    git clone <repository_url>
    cd mcp_stock
    
  2. Create a virtual environment (recommended):

    python -m venv venv
    source venv/bin/activate
    
  3. Install dependencies:

    Install the required packages using pip:

    pip install -r requirements.txt
    playwright install
    
  4. Configuration:

    Some tools might require API keys or other configuration. Please refer to the config.py file and potentially create a .env file if necessary (based on os.getenv usage in server.py).

    TAVILY_API_KEY=
    
  5. Run the server:

    You can run the server using the server.py script. The server will listen on the port specified by the PORT environment variable, defaulting to 8000.

    fastmcp run server.py --transport=sse --port=8000 --host=0.0.0.0
    

    To run on a specific port:

    fastmcp run server.py --transport=sse --port=8000 --host=0.0.0.0
    

Usage

Once the server is running, you can interact with the tools via the /mcp prefix followed by the tool's mount path (e.g., /mcp/stock, /mcp/finance). The specific endpoints and expected parameters for each tool can be found by examining the tool definitions within each tool's Python file.

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