simulate_montecarlo
Single-factor Monte Carlo (6 distributions)
How to use it
Project documentation lists simulate_montecarlo for the Oraclaw MCP server. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf and others), then check which tools your installed version makes available. Tool availability can depend on configuration and credentials. A server handshake does not verify this tool’s behavior. See the full listing for setup details.
Install Oraclaw
npm install @oraclaw/banditOther tools in Oraclaw (16)
PageRank, Louvain communities, bottleneck detection
VaR and CVaR (Expected Shortfall)
Z-Score + IQR anomaly detection
UCB1 / Thompson / Epsilon-Greedy arm selection
CMA-ES continuous black-box optimization
Context-aware LinUCB bandit
Genetic algorithm for discrete + multi-objective problems
A + Yen's k-shortest paths
Beta posterior update from weighted evidence
Multi-model consensus + uncertainty decomposition
ARIMA + Holt-Winters time series forecasting
Brier + log score for forecaster accuracy
Multi-source probability consensus (Hellinger)
What-if comparison + sensitivity ranking
LP / MIP / QP solver via HiGHS (provably optimal)
Energy-matched task scheduling