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749,745 tools. Updated 2026-11-06 04:06

"A tool for backtesting trading strategies on historical data and analyzing performance metrics" matching MCP tools:

  • Retrieves historical candlestick data for technical analysis, identifying support/resistance levels, calculating indicators, and backtesting strategies.
    MIT
  • Analyze historical price data for technical analysis and trading decisions. Calculate indicators, identify support/resistance levels, and backtest strategies using candlestick data.
    MIT
  • Retrieve aggregated health status, performance metrics, alerts, and historical trends for the backtesting system to monitor system health and performance.
    MIT
  • Get a full trading journal overview in one call: performance metrics, Edge Score, equity curve, open positions, and account details for a window.
    MIT

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  • Run several trading strategies on identical data and view side-by-side comparisons, with support for benchmarks and adjustable result detail.
    MIT
  • Rank published backtested strategies by Rozkoduj Score, annualized USD returns, or recency. Filter by trading symbol to find top-performing strategies for a specific instrument.
    MIT
  • Retrieve OHLCV candlestick data for a trading pair to analyze price trends, create charts, compute indicators, or backtest strategies.
    Go
    MIT
  • Run a historical backtest to evaluate trading strategies using OHLCV data or signal series, with configurable execution settings and detailed performance metrics.
    MIT
  • Check which portfolio trading rules trigger on today's real market data. Uses actual historical prices, returns triggered flags, actions, and recommended weights for daily monitoring.
    MIT
  • Run historical backtests of trading rules on real market data to evaluate performance, monthly returns, drawdown, turnover, and transaction costs.
    MIT
  • Retrieve real-time trading metrics for all four live Tradovate bots in one call, including daily P&L, win rates, signals, error states, and validation badges from real log data.
    MIT
  • Fetch live stock price, market cap, performance, and SEC-filing metrics for any public ticker, returning only requested data with cited sources.
    MIT
  • Get up to six Aurora-recommended strategies by bot type across multiple symbols. Browse options before picking a specific trading symbol.
    MIT
  • Fetch and filter your Bybit trading strategies by status, symbol, type, or time range. Monitor active strategies, inspect stopped ones, and paginate through large result sets.
    MIT
  • Retrieve historical implied volatility for options with hourly granularity to analyze trends, compare averaging periods, and support backtesting or risk management.
    MIT
  • Discover available endpoints, metrics, parameters, and conventions in Trading Volatility v2. Call this first to self-orient before making other data requests.
    MIT
  • Retrieve raw performance metrics for any tool, including invocation counts, p50/p95/p99 latency, error rate, and uptime. Use these figures to diagnose performance issues and guide optimization.
    MIT