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.
Enables AI-driven quant research by exposing backtesting, portfolio optimization, and performance analytics tools through MCP, allowing iterative strategy refinement with built-in overfitting guardrails.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
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 AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.
An MCP server exposing a registry of paper-backed quantitative trading methods plus a deterministic, no-LLM decision helper for reproducible trading research.
