AKShare MCP Server
by ttjslbz001
The AKShare MCP Server provides financial data analysis capabilities using the AKShare library. It integrates with Claude Desktop via the Model Context Protocol (MCP).
Last updated: N/A
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
- 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>"
}
}
}
- Restart Claude Desktop
- 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:
-
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
-
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"
-
Import the new function in
src/mcp_server_akshare/server.py
:from .api import ( # Existing imports... fetch_new_data_function, )
-
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 }, ),
-
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, )
-
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