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.
Enables MCP-compatible AI agents to retrieve quantum-computed portfolio optimisation, VaR simulations, AI-enhanced sentiment and regime detection, and cross-asset risk signals through simple metric tools.
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.