iflow-mcp_parsedark-mcp_stock 0.1.0

Stock Analysis MCP Server - Provides various tools for accessing and analyzing stock market data

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.