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AKShare Financial Data

STDIO

MCP server providing financial data analysis capabilities using AKShare library.

AKShare MCP Server

A Model Context Protocol (MCP) server that provides financial data analysis capabilities using the AKShare library.

Features

  • Access to Chinese and global financial market data through AKShare
  • Integration with Claude Desktop via MCP protocol
  • Support for various financial data queries and analysis

Installation

Using uv (recommended)

# Clone the repository git clone https://github.com/yourusername/akshare_mcp_server.git cd akshare_mcp_server # Create and activate a virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install dependencies with uv uv pip install -e .

Using pip

# Clone the repository git clone https://github.com/yourusername/akshare_mcp_server.git cd akshare_mcp_server # Create and activate a virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install dependencies pip install -e .

Usage

Running the server

# Activate the virtual environment source venv/bin/activate # On Windows: venv\Scripts\activate # Run the server python run_server.py

Integrating with Claude Desktop

  1. Add the following configuration to your Claude Desktop configuration:
"mcpServers": { "akshare-mcp": { "command": "uv", "args": [ "--directory", "/path/to/akshare_mcp_server", "run", "akshare-mcp" ], "env": { "AKSHARE_API_KEY": "<your_api_key_if_needed>" } } }
  1. Restart Claude Desktop
  2. Select the AKShare MCP server from the available tools

Available Tools

The AKShare MCP server provides the following tools:

  • Stock data queries
  • Fund data queries
  • Bond data queries
  • Futures data queries
  • Forex data queries
  • Macroeconomic data queries
  • And more...

Adding a New Tool

To add a new tool to the MCP server, follow these steps:

  1. Add a new API function in src/mcp_server_akshare/api.py:

    async def fetch_new_data_function(param1: str, param2: str = "default") -> List[Dict[str, Any]]: """ Fetch new data type. Args: param1: Description of param1 param2: Description of param2 """ try: df = ak.akshare_function_name(param1=param1, param2=param2) return dataframe_to_dict(df) except Exception as e: logger.error(f"Error fetching new data: {e}") raise
  2. Add the new tool to the enum in src/mcp_server_akshare/server.py:

    class AKShareTools(str, Enum): # Existing tools... NEW_TOOL_NAME = "new_tool_name"
  3. Import the new function in src/mcp_server_akshare/server.py:

    from .api import ( # Existing imports... fetch_new_data_function, )
  4. Add the tool definition to the handle_list_tools() function:

    types.Tool( name=AKShareTools.NEW_TOOL_NAME.value, description="Description of the new tool", inputSchema={ "type": "object", "properties": { "param1": {"type": "string", "description": "Description of param1"}, "param2": {"type": "string", "description": "Description of param2"}, }, "required": ["param1"], # List required parameters }, ),
  5. Add the tool handler in the handle_call_tool() function:

    case AKShareTools.NEW_TOOL_NAME.value: param1 = arguments.get("param1") if not param1: raise ValueError("Missing required argument: param1") param2 = arguments.get("param2", "default") result = await fetch_new_data_function( param1=param1, param2=param2, )
  6. Test the new tool by running the server and making a request to the new tool.

Development

# Install development dependencies uv pip install -e ".[dev]" # Run tests pytest

Docker

You can also run the server using Docker:

# Build the Docker image docker build -t akshare-mcp-server . # Run the Docker container docker run -p 8000:8000 akshare-mcp-server

License

MIT

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