Enables AI agents to run WorldQuant BRAIN alpha backtests via MCP, supporting expression submission, status tracking, result analysis, and batch resumption.
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 agents to operate a local financial terminal, including market data, backtesting, paper portfolio management, and news digest, through safe, gated tools over MCP.
MCP server that exposes TradingAgents multi-agent financial research as async tasks, generating research reports and non-executive decisions for LLM hosts without touching trading accounts.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.