Qanat

MIT MCP for quant factor processing and backtesting

AI Agents / Agents · OSS/MIT · 315

Reviewed 2026-10-04 · last push 2026-10-19 · repo checked 2026-10-19

What's Good

MIT (fidetolabs/qanat). PyPI `qanat-fdtl` v0.3.0 (HTTP 200). `uv tool install qanat-fdtl` then `qanat init --demo` builds synthetic strategies with no network/key; `qanat mcp` for Claude Code and other clients; optional Streamable HTTP. Aimed at daily/weekly rebalance horizons. ★~287.

The Catch

Beta quant niche — not a general agent framework. Your real market data sources may need keys/network even though Qanat itself makes no calls. Vs generic data MCP / notebook stacks: catch is factor pipeline + backtest priced after fees, exposed only through MCP. Pin PyPI; demo data is synthetic.

Verdict

MIT quant factor MCP when agents should operate a backtest store — not a general RAG/data MCP; bring your own market sources beyond demo.

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