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.
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 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.
The MCP server for AlphaForge — the agent-native quant CLI: write strategies in JSON, optimize with Optuna TPE, validate with walk-forward, export to TradingView Pine v6. This server lets your AI agent drive the whole pipeline over MCP.