Tushare Mcp Server — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Tushare Mcp Server (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A Model Context Protocol (MCP) server that provides AI assistants with access to Tushare financial data API. This enables AI models to query Chinese stock market data, financial statements, macroeconomic indicators, and more.
This MCP server exposes 18 financial data tools across multiple categories:
git clone https://github.com/lijinly/tushare-mcp-server.git
cd tushare-mcp-server
pip install -e .Register at Tushare Pro and get your API token from your profile page.
# Linux/macOS
export TUSHARE_TOKEN="your_token_here"
# Windows PowerShell
$env:TUSHARE_TOKEN="your_token_here"
# Windows CMD
set TUSHARE_TOKEN=your_token_hereAdd to your MCP client configuration (e.g., Claude Desktop, Cline):
{
"mcpServers": {
"tushare": {
"command": "python",
"args": ["-m", "tushare_mcp_server"],
"env": {
"TUSHARE_TOKEN": "your_token_here"
}
}
}
}Claude Desktop Config Location:
%APPDATA%\Claude\claude_desktop_config.json~/Library/Application Support/Claude/claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonpython -m tushare_mcp_serverOnce configured, the AI assistant can directly call Tushare data tools:
Example queries:
All tools return JSON formatted data:
{
"data": [...],
"count": 100,
"columns": ["ts_code", "trade_date", "close", "pe", "pb"]
}tushare-mcp-server/
├── src/tushare_mcp_server/
│ ├── __init__.py
│ ├── __main__.py
│ └── server.py # Main MCP server implementation
├── pyproject.toml # Project configuration
├── README.md
└── .gitignore| Package | Version | Purpose |
|---|---|---|
| mcp | >=1.0.0 | MCP protocol implementation |
| tushare | >=1.4.0 | Tushare API client |
| pandas | >=2.0.0 | Data manipulation |
# Create virtual environment
conda create -n tushare-mcp python=3.10 -y
conda activate tushare-mcp
# Install in editable mode
pip install -e .python -m tushare_mcp_serverMake sure you've set the TUSHARE_TOKEN environment variable before starting the server.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.