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

Related MCP server: MCP-BOS

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 :
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 :
class AKShareTools(str, Enum): # Existing tools... NEW_TOOL_NAME = "new_tool_name"
Import the new function in :
from .api import ( # Existing imports... fetch_new_data_function, )
Add the tool definition to the :
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 :
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.