Grade a same-game combo quote against fair value using leg prices and true win probability. Get expected value, correlation trap flag, and verdict from SMASH to RUN.
MIT
342,772 tools. Last updated 2026-07-30 12:15
"Qwant" matching MCP tools:
- Convert between implied probability, American odds, and decimal odds. Input any one format to get all three.MIT
- Update a prior probability with new evidence using Bayes theorem. Provide prior and evidence likelihoods to get posterior and step-by-step chain.MIT
- Compute expected-value edge on prediction market contracts. Input market price and your probability estimate to get edge percentage and a clear action signal.MIT
- Calculate the optimal dollar stake for a prediction-market contract using the Kelly criterion. Input your win probability, market price, and bankroll to get position size and risk rating.MIT
- Compare a market price to historical base rates to compute the gap, assess signal quality, and detect when markets diverge from historical frequency.MIT
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Matching MCP Connectors
The Brain Layer for AI Trading Agents — quant calls + cross-venue arb across perp venues via MCP.
Quant finance tools: stock analysis, options IV, Monte Carlo, AI prediction, risk scan, backtests.
- Aggregates AI prediction, implied volatility, options pressure, Monte Carlo simulation, and strategy backtesting into a single bull/bear signal with supporting evidence for any US stock ticker.MIT
- Retrieve backtested equity curves and performance metrics for quantitative strategies on a single stock. Evaluate momentum, mean-reversion, and vol-targeting with Sharpe, Sortino, and max drawdown.MIT
- Identify max-pain, gamma walls, and expected move from options positioning to find price magnets and support/resistance levels for any US stock or ETF.MIT
- Generate a structured market research report for a stock, combining AI predictions, volatility analysis, options positioning, Monte Carlo outlook, and strategy backtests into a single markdown document.MIT
- Generate chart image URLs for a stock: price chart, IV surface, and options flow heatmap. Use to accompany analysis with supporting visuals.MIT
- Run a Monte Carlo simulation to generate probabilistic price ranges and quantify downside risk for a stock over a 30-day horizon.MIT
- Get a data-driven probability estimate for the next trading day's direction using an ensemble of gradient-boosted trees, LSTM, and quantum-classical hybrid models. Delivers up/down prediction, confidence, and model votes.MIT
- Assess pre-trade risk for adding a stock to a portfolio: evaluate volatility, beta, VaR, drawdown, market regime, return distribution, position sizing, sector exposure, and correlation with holdings.MIT
- Assess whether options are cheap or expensive using IV rank and percentile. Determine volatility regime and risk-reversal direction for strategy selection.MIT
- Backtest a quantitative trading method using its own live signal logic bar by bar, applying realistic costs and returning performance stats for parameter validation.MIT
- Fetch recent news headlines for a US stock ticker. Returns titles, summaries, publication dates, and providers without sentiment analysis, enabling the agent to derive its own sentiment.MIT
- Retrieve full details and citations for a registered quantitative trading method, including paper reference, regime applicability, and mechanical description. Choose markdown or JSON output.MIT
- Classifies a US equity ticker's market regime by computing its daily Hurst exponent: H>=0.55 trending, H<=0.45 mean-reverting, else random walk.MIT
- Decide ENTRY or NO_ENTRY by scoring trading setups with a deterministic composite of reward:risk, regime strength, volume, RSI, and stop quality. Optionally applies news sentiment boost or veto. Returns position sizing and execution plan.MIT