Enables AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.
Enables quantitative trading research by providing tools to backtest strategies, list market datasets, review forward-test logs, and search previously rejected hypotheses, all through an MCP interface.
An extensible framework that exposes quantitative research functions and financial data connectors, such as FRED, via an MCP server. It enables users to perform complex financial modelling, data retrieval, and autonomous research loops with built-in guardrails and pluggable components.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
Provides point-in-time financial data access and an honest backtesting engine via MCP, enabling users to research restated fundamentals, run backtests with deflated Sharpe metrics, and benchmark returns against published factors.