Noon Barbari Backtesting

Crypto backtesting tools: real backtests with robustness verdicts, daily signals and market data.

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Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
85%
Qualität der Benennung
98%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,720Tokens (Tool-Definitionen)
~799 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.34% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "backtesting": {
      "url": "https://noonbarbari.xyz/mcp"
    }
  }
}

Remote-Endpunkte

https://noonbarbari.xyz/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (11)

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🟢list_strategies

List the strategy templates available for backtesting and comparison (name, title, one-line description). Use the returned `name` value as the strategy identifier in other tools.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_coin_signals(coin)

Today's daily-bar indicator readings for crypto coins, computed by a real backtesting engine from Binance closes: price, RSI-14, MACD state, SMA 50/200 posture, SuperTrend, Bollinger position, ATR volatility, 52-week range. Pass a coin ticker (e.g. 'btc') for one coin, or omit for the whole 50-coin board.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "coin": {
      "type": "string",
      "description": "Lower-case ticker, e.g. btc, eth, sol. Omit for all coins."
    }
  },
  "additionalProperties": false
}
🟢get_buy_hold(coin)

What a $1,000 buy of a coin on Jan 1 of each available year would be worth today — ROI, peak value and date, and the maximum drawdown endured along the way. Real Binance data, refreshed daily.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "coin": {
      "type": "string",
      "description": "Lower-case ticker, e.g. btc, eth, sol."
    }
  },
  "required": [
    "coin"
  ],
  "additionalProperties": false
}
🟢get_overfitting_index

The Crypto Overfitting Index: the monthly share (%) of default-parameter strategy configurations (10 templates × 50 coins) whose out-of-sample Sharpe turned negative — how much of what backtests promise fails on unseen data. Returns the current reading and full history.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢compare_strategies(strategy_a, strategy_b)

Head-to-head comparison of two strategy templates from real monthly engine runs across ~50 coins: per-coin win count, median out-of-sample Sharpe, survival counts, median return and drawdown. Use strategy names from list_strategies (e.g. 'super_trend', 'ema_crossover').

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "strategy_a": {
      "type": "string",
      "description": "First strategy name, e.g. super_trend"
    },
    "strategy_b": {
      "type": "string",
      "description": "Second strategy name, e.g. ema_crossover"
    }
  },
  "required": [
    "strategy_a",
    "strategy_b"
  ],
  "additionalProperties": false
}
🟢search_answers(query)

Search Noon Barbari's Q&A knowledge base of direct, data-grounded answers about backtesting, overfitting, validation, indicators, risk management and crypto markets. Returns the top matching questions with their full answers.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Free-text query, e.g. 'why do backtests fail'"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
⚪run_backtest(strategy, start_date, starting_cash)

Run a real backtest of a strategy template on BTC/USDT from a start date (public what-if engine; may take up to a minute on a cache miss; rate-limited). Returns net return, max drawdown, trade count, a robustness score with an overfitting verdict, and a shareable result URL.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "strategy": {
      "type": "string",
      "description": "Strategy name from list_strategies, e.g. super_trend"
    },
    "start_date": {
      "type": "string",
      "description": "ISO date, e.g. 2022-01-01 (2020-01-01 or later)"
    },
    "starting_cash": {
      "type": "number",
      "description": "Starting balance in USD (default 10000, max 1000000)"
    }
  },
  "required": [
    "strategy",
    "start_date"
  ],
  "additionalProperties": false
}
🟢get_dca(coin, amount, frequency, start_date)

Dollar-cost-averaging outcome for a coin: what buying a fixed dollar amount on a schedule (weekly or monthly) since a start date would be worth today — total invested, units, average cost, current value and ROI — plus the lump-sum comparison and the worst drawdown endured. Real Binance closes, refreshed daily.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "coin": {
      "type": "string",
      "description": "Lower-case ticker, e.g. btc, eth, sol."
    },
    "amount": {
      "type": "number",
      "description": "USD invested per purchase (default 100)."
    },
    "frequency": {
      "type": "string",
      "enum": [
        "weekly",
        "monthly"
      ],
      "description": "Purchase cadence (default weekly)."
    },
    "start_date": {
      "type": "string",
      "description": "ISO date to start buying from, e.g. 2021-01-01 (optional; default = full history)."
    }
  },
  "required": [
    "coin"
  ],
  "additionalProperties": false
}
🟢check_overfitting(sharpe, timeframe, length_days, n_trials, skew, ...)

Compute the Deflated Sharpe Ratio (Bailey & Lopez de Prado 2014) for YOUR OWN backtest: given its annualised Sharpe, length, and how many strategy variants you tried before selecting it, returns the probability the result is real skill rather than selection luck, the luck bar it must clear, and a plain verdict. Works on any backtest, not just ours.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "sharpe": {
      "type": "number",
      "description": "Annualised Sharpe ratio of the selected backtest."
    },
    "timeframe": {
      "type": "string",
      "enum": [
        "1h",
        "4h",
        "1d",
        "1w"
      ],
      "description": "Bar timeframe of the returns (default 1d)."
    },
    "length_days": {
      "type": "number",
      "description": "Length of the backtest in calendar days."
    },
    "n_trials": {
      "type": "number",
      "description": "How many strategy/parameter variants were tried before picking this one."
    },
    "skew": {
      "type": "number",
      "description": "Skewness of the return series (default 0)."
    },
    "kurtosis": {
      "type": "number",
      "description": "Non-excess kurtosis of returns (Gaussian = 3, the default)."
    }
  },
  "required": [
    "sharpe",
    "length_days",
    "n_trials"
  ],
  "additionalProperties": false
}
🟢query_dataset(template, coin)

Query our open 11,440-run curve-fitting study (10 strategy templates x 20 coins, 70/30 in-sample/out-of-sample split). Returns the headline overfitting stats and the tuned picks matching an optional template and/or coin filter — each with in-sample vs out-of-sample Sharpe, the Sharpe haircut, and the in-sample-to-out-of-sample parameter rank correlation.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "template": {
      "type": "string",
      "description": "Strategy name, e.g. super_trend (optional). Omit for all templates."
    },
    "coin": {
      "type": "string",
      "description": "Ticker, e.g. btc (optional). Omit for all coins."
    }
  },
  "additionalProperties": false
}
🟢search_glossary(query)

Search Noon Barbari's trading glossary for a plain-language definition of an indicator, metric or concept (RSI, MACD, Sharpe ratio, drawdown, walk-forward, overfitting, and 60+ more). Returns the top matching terms with a short definition, the full explanation, and a link.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "A term or question, e.g. 'deflated sharpe' or 'what is RSI'."
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}

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