exposes a remote MCP endpoint so agents can:
run strategy backtests by symbol/timeframe/date range,
pass strategy inputs programmatically,
receive structured backtest results (trades, win rate, profit, drawdown),
keep long-running runs observable via progress notifications,
support Binance Futures tickers only,
enforce a maximum of 1440 candles per backtest,
apply a rate limit of 3 backtests per
MCP server that exposes the Backtest360 backtesting engine API as tools, enabling AI agents to conversationally discover indicators, build and validate strategies, run backtests, and read results.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
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.