# Python 3.10+（推荐 3.12）
pip install pyqlib mcp

python -m qlib.run.get_data qlib_data \
  --target_dir ~/.qlib/qlib_data/cn_data \
  --region cn

{
  "mcpServers": {
    "qlib": {
      "command": "python",
      "args": ["/path/to/qlib-mcp/server.py"],
      "description": "Microsoft Qlib 量化研究平台"
    }
  }
}

调用 qlib_init，data_path = "~/.qlib/qlib_data/cn_data"，region = "cn"

调用 qlib_list_instruments，market = "csi300"，start_date = "2024-01-01"

调用 qlib_get_data，symbols = "SZ000001"，fields = "$close,$volume"，start_date = "2024-10-01"

调用 qlib_factor_analysis，factor_expr = "$close / Ref($close, 20) - 1"

调用 qlib_backtest_topk，market = "csi300"，topk = 50，signal_field = "$close / Ref($close, 20) - 1"

# 价格动量
$close / Ref($close, 20) - 1      # 20 日动量

# 技术指标
EMA($close, 12) - EMA($close, 26) # MACD
($close - Mean($close, 20)) / Std($close, 20)  # 布林带位置

# 成交量因子
$volume / Mean($volume, 20)        # 相对成交量
Corr($close, $volume, 10)          # 价量相关性（聪明钱）