Provides 11 tools for stock research, including search, market history, financial statements, announcements, and data quality checks, with a local-first architecture using DuckDB and Parquet.
Local-first backtesting engine with built-in overfitting detection (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents to validate trading strategies.
Enables LLMs to retrieve, analyze, and visualize stock prices and financial report data for quantitative trading research and investment analysis. Provides real-time and historical stock data, financial statement analysis, key metric calculations, and trading signal visualization.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
Enables AI assistants to backtest trading strategies described in plain English, providing access to market data, technical indicators, and comprehensive performance reports.