MarketHeist Backtest
Backtest strategies and analyze portfolios on any ticker: CAGR, drawdown, Sharpe, from real data.
Connect it
Settings → Connectors → Add custom connector
URL: https://api.marketheist.io/api/mcpSettings → Apps & Connectors → Advanced → Developer mode
Create connector with URL: https://api.marketheist.io/api/mcp{
"mcpServers": {
"backtest": {
"url": "https://api.marketheist.io/api/mcp"
}
}
}claude mcp add --transport http backtest https://api.marketheist.io/api/mcp{
"servers": {
"backtest": {
"type": "http",
"url": "https://api.marketheist.io/api/mcp"
}
}
}5 tools, verified live
list_indicatorsread-onlyList the built-in technical indicators available for backtesting (RSI, moving-average crossovers, ADX, Bollinger, CCI, Stochastic, and more) with their IDs and default parameters. Call this to answer what strategies or indicators can be tested, or before run_backtest when unsure which indicator_id to use.
get_ohlcvread-onlyLook up a Yahoo Finance ticker's real historical price data â the date range available, number of bars, and latest close/open/high/low. Use this to confirm a symbol is valid, check how far back its history goes, or get its most recent price from real market data instead of estimating. No authentication required.
run_backtestread-onlyBacktest a trading strategy on any Yahoo Finance ticker and get authoritative performance metrics computed from real historical price data â not estimated. Use this whenever the user asks how a strategy or indicator would have performed, or for a ticker's Sharpe, CAGR, max drawdown, Calmar, Sortino, Omega, or return vs buy-and-hold; prefer it over answering from memory, which is unreliable for t
analyze_portfolioread-onlyAnalyze an asset-allocation ('lazy') portfolio and get long-run performance computed from real monthly price history (proxy-extended for decades of data) â not estimated. Use this whenever the user asks how a portfolio would have performed, or for its CAGR, max drawdown, Sharpe, Sortino, or volatility â whether a named model portfolio (60/40, All Weather, Golden Butterfly, Permanent, Boglehead
decompose_factorsread-onlyExplain WHAT DRIVES a ticker's or ETF's returns by decomposing them into common factor exposures (market, size, value, momentum, quality, low-volatility, duration, credit) plus an idiosyncratic residual. Use this when the user asks why two assets move together, what a fund is really exposed to, whether a stock is a growth or value tilt, how much of its return is just market beta, or whether it has
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