io.github.koreal6803/finlab-ai MCP Server

io.github.koreal6803/finlab-ai

Quantitative trading toolkit with 900+ data columns, backtesting, and 60+ strategy examples for AI-driven alpha discovery.

Repository Registry

What is the io.github.koreal6803/finlab-ai MCP server?

FinLab AI is a quantitative trading toolkit that provides access to 900+ financial data columns, backtesting capabilities, and 60+ pre-built strategy examples. It enables AI agents to discover trading strategies, analyze stock evidence, and explore factor-based approaches for Taiwan stock markets.

FinLab AI gives you a complete quantitative trading environment accessible via MCP. Query financial data across 80+ tables, backtest strategies with the sim() API, explore 60+ example strategies with Python code, and leverage factor engineering for stock selection. It's designed for researchers and traders building data-driven trading systems.

How to install io.github.koreal6803/finlab-ai

Copy-paste configuration for popular MCP clients.

transport: http

Config generated by PluginBench — verify against the source before use.

~/.cursor/mcp.json

{
  "mcpServers": {
    "finlab-ai": {
      "url": "https://mcp.finlab.finance/mcp"
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

list_strategies — List available pre-built strategy examples
get_strategy — Retrieve a specific strategy with its Python code
get_stock_evidence — Get evidence and analysis for stock selection
get_data_catalog — Browse the 900+ available data columns across 80+ tables
get_finlab_docs — Access FinLab AI documentation, always in sync with the main repository
how_to_start — Get guidance on getting started with FinLab AI

Use cases

Backtest quantitative trading strategies on Taiwan stock data using the sim() API
Discover factor-based stock selection signals from 900+ financial data columns
Explore and adapt 60+ pre-built strategy examples with Python code
Analyze stock evidence and multi-factor composites for portfolio construction
Research strategy performance metrics (CAGR, Sharpe ratio, max drawdown) on historical data

io.github.koreal6803/finlab-ai MCP server FAQ

What is FinLab AI?

FinLab AI is a quantitative trading toolkit that provides access to 900+ financial data columns, backtesting capabilities, and 60+ strategy examples. It helps AI agents discover trading strategies and analyze stock markets, primarily focused on Taiwan stocks.

How do I install FinLab AI?

You can use the automated installer: `curl -sSf https://ai.finlab.finance/install.sh | sh`. Alternatively, use the hosted MCP server without installation: `claude mcp add --transport http finlab https://mcp.finlab.finance/mcp`

Is FinLab AI free?

The README does not specify pricing details. The hosted MCP server is available as a read-only service, but you should check finlab.finance for current pricing and terms.

What data is available?

FinLab AI provides 900+ data columns across 80+ tables, including stock prices, factors, and fundamental data. The get_data_catalog tool lets you browse all available data.

Can I backtest strategies?

Yes. FinLab AI includes a backtesting API (sim()) with support for resampling and metrics like CAGR, Sharpe ratio, and max drawdown. You can test your own strategies or adapt from 60+ examples.

Does it require authentication?

The hosted MCP server is read-only and available at https://mcp.finlab.finance/mcp. No authentication details are mentioned in the README.

README (reference)

Source of truth, from the repository.

FinLab AI

Let AI discover your next alpha.

FinLab AI is an official product of FinLab. FinLab official website: https://finlab.finance

Installation

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.

MCP Server

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.

Documentation

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

Learn more

Quant trading guide (量化交易): what quantitative trading is, a Taiwan-stock strategy backtester, and a platform comparison.
Program trading guide (程式交易): how program trading works, three backtest-verified Taiwan-stock strategies, and an auto-trading walkthrough.
Stock selection guide (股票選股): factor-based stock picking with real backtests, from single factors to multi-factor composites.
Strategy research blog: backtest-verified Taiwan-stock strategy reports (CAGR, Sharpe, max drawdown).
Website: finlab.finance

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