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293,268 tools. Last updated 2026-07-13 06:09

"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
  • Retrieve aggregated health status, performance metrics, alerts, and historical trends for the backtesting system to monitor system health and performance.
    MIT
  • Retrieve current stock metrics for any public company, including price, market cap, performance, and financials from verified official sources.
    MIT
  • Run several trading strategies on identical data and view side-by-side comparisons, with support for benchmarks and adjustable result detail.
    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

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  • Query historical implied volatility data for options with hourly granularity, supporting up to 2 years of data and customizable averaging periods for backtesting and analysis.
    MIT
  • Returns up to six Aurora-recommended strategies for a given bot type. Use it to browse trading strategies without first selecting a symbol.
    MIT
  • Retrieve historical index price klines derived from composite spot prices across multiple exchanges for research, backtesting, or basis analysis.
    MIT
  • List Rozkoduj's published trading strategies with key performance metrics. Sort by score, APY, or recency to identify top performers.
    MIT
  • Evaluate predictive query performance by comparing predictions with known historical labels, returning metrics for classification, regression, or link prediction tasks.
    MIT
  • Retrieve historical mark price klines for derivative contracts to analyze margin requirements and liquidation risk. Use for risk management and backtesting.
    MIT
  • Retrieve computed market metrics including volume averages, volatility, SMAs, and trend direction for a stock to analyze trading patterns and technical indicators beyond the basic quote.
    MIT
  • Test cryptocurrency trading strategies (SMA cross, RSI, MACD, Bollinger breakout) on historical data with customizable periods and timeframes, returning performance metrics and equity curves.
    MIT
  • Backtest trading strategies on historical stock data, evaluating performance with institutional-grade metrics. Supports RSI, MACD, Bollinger Bands, and other strategies.
    MIT