
This quantitative trading toolkit gives Claude direct access to 900+ financial data columns across 80+ tables, a backtesting engine via the sim() API, and 60+ ready to use strategy examples. You can ask Claude to explore factor data, backtest trading ideas with custom resampling and metrics, or adapt ML reference patterns for feature engineering. The included documentation covers everything from data schema to anti-patterns, so Claude can help you prototype strategies without constantly context switching to docs. Reach for this when you want to iterate on quant ideas conversationally rather than writing boilerplate backtest code from scratch.
Let AI discover your next alpha.
FinLab AI is an official product of FinLab. FinLab official website: https://finlab.finance
curl -sSf https://ai.finlab.finance/install.sh | sh
Auto-detects your CLI (Claude Code / Codex / Gemini), installs uv if needed, and sets up the skill.
A hosted, read-only MCP server (streamable HTTP) is available — no install required:
claude mcp add --transport http finlab https://mcp.finlab.finance/mcp
Tools: list_strategies, get_strategy (with Python code), get_stock_evidence, get_data_catalog, get_finlab_docs (this skill's docs, always in sync with main), how_to_start. Listed on the MCP Registry as io.github.koreal6803/finlab-ai (see server.json). The old finlab-ai.koreal6803.workers.dev endpoint is retired.
| Document | Content |
|---|---|
| Data Reference | 900+ columns across 80+ tables |
| Backtesting Reference | sim() API, resampling, metrics |
| Factor Examples | 60+ complete strategy examples |
| Best Practices | Patterns, anti-patterns, tips |
| ML Reference | Feature engineering, labels |