307,569 tools. Last updated 2026-07-18 19:54
"author:Khuong-Quan-Nguyen" matching MCP tools:
- Evaluate a same-game combo parlay on prediction markets by comparing its offered odds to fair value. Input leg prices and your true win probability to get expected value and a verdict.MIT
- Convert between implied probability, American odds, and decimal odds. Input any single format to get the equivalent in all three.MIT
- Compute posterior probability by updating a prior with one or more pieces of evidence using Bayes' theorem, useful for adjusting estimates in prediction markets.MIT
- Calculate the expected-value edge on any Kalshi or Polymarket contract by comparing market price to your probability estimate, returning the percentage edge and a clear buy/sell/skip signal.MIT
- Calculate optimal stake for prediction markets using win probability, market price, and bankroll. Returns dollar amount and risk rating.MIT
- Compare a prediction market price to a historical base rate to identify mispricing. Get the percentage point gap, directional signal, and sample quality.MIT
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- 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
- Record a student's study visit to a knowledge graph node after a lesson, updating mastery score from quiz results or manual input to track learning progress.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
- Retrieve complete details of a knowledge graph node, including description, related concepts, learning resources, and student mastery statistics, using its node ID.MIT
- Extract key concepts and prerequisite relationships from educational texts to expand a knowledge graph. Analyzes textbooks, lectures, or handouts for automatic KG node addition.MIT
- Assess whether options are cheap or expensive using IV rank and percentile. Determine volatility regime and risk-reversal direction for strategy selection.MIT
- Find educational concepts in AeroEdu's Knowledge Graph via natural language queries, returning descriptions, subject, grade, difficulty, and linked nodes.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