📌Overview

Purpose: To provide financial data analysis capabilities through a Model Context Protocol (MCP) server using the AKShare library.

Overview: The AKShare MCP server serves as an accessible platform for analyzing both Chinese and global financial market data. It integrates seamlessly with Claude Desktop, allowing users to query various financial data and perform analyses effortlessly.

Key Features:

• Comprehensive Data Access: Offers extensive data coverage from Chinese and global financial markets, enabling diverse queries and analyses using AKShare.

• MCP Integration: Facilitates integration with Claude Desktop via the MCP protocol, enhancing user experience by centralizing tool access within an existing interface.

• Versatile Query Support: Supports a wide range of financial queries, including stock, fund, bond, futures, forex, and macroeconomic data.

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AKShare MCP Server

A Model Context Protocol (MCP) server providing 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)

git clone https://github.com/yourusername/akshare_mcp_server.git
cd akshare_mcp_server

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

uv pip install -e .

Using pip

git clone https://github.com/yourusername/akshare_mcp_server.git
cd akshare_mcp_server

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

pip install -e .

Usage

Running the server

source venv/bin/activate  # On Windows: venv\Scripts\activate

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>"
        }
    }
}

2. Restart Claude Desktop
3. 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"],
       },
   ),
   

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

uv pip install -e ".[dev]"

pytest

Docker

Run the server with Docker:

docker build -t akshare-mcp-server .

docker run -p 8000:8000 akshare-mcp-server

License

MIT