predict_ensemble

MCP tool from Oraclaw by Whatsonyourmind

Multi-model consensus + uncertainty decomposition

How to use it

Project documentation lists predict_ensemble 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/bandit
FULL ORACLAW LISTING

Other tools in Oraclaw (16)

analyze_graph

PageRank, Louvain communities, bottleneck detection

analyze_risk

VaR and CVaR (Expected Shortfall)

detect_anomaly

Z-Score + IQR anomaly detection

optimize_bandit

UCB1 / Thompson / Epsilon-Greedy arm selection

optimize_cmaes

CMA-ES continuous black-box optimization

optimize_contextual

Context-aware LinUCB bandit

optimize_evolve

Genetic algorithm for discrete + multi-objective problems

plan_pathfind

A + Yen's k-shortest paths

predict_bayesian

Beta posterior update from weighted evidence

predict_forecast

ARIMA + Holt-Winters time series forecasting

score_calibration

Brier + log score for forecaster accuracy

score_convergence

Multi-source probability consensus (Hellinger)

simulate_montecarlo

Single-factor Monte Carlo (6 distributions)

simulate_scenario

What-if comparison + sensitivity ranking

solve_constraints

LP / MIP / QP solver via HiGHS (provably optimal)

solve_schedule

Energy-matched task scheduling