Whatsonyourmind/oraclaw

Deterministic decision-intelligence MCP server for AI agents — 17 tools (bandits/LinUCB, HiGHS LP/MIP, PageRank, Monte Carlo, CMA-ES, conformal). Sub-25ms. Zero LLM cost. 11 free, no key. Listed on the MCP Registry & Glama.

This repository also configures its own agents. See what oraclaw tells them →

13Stars on the repository
16Mods indexed here, across every type
2d agoLast push, which is what freshness is scored on
MITLicence, which decides whether bodies are shown

oraclaw-anomaly

01

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Anomaly detection for AI agents. Z-score, IQR, and streaming detection. Find outliers in data instantly. Sub-millisecond response. Works on single values or full datasets.

not rated 13 2d ago A SkillSpector: pass 43 tokens original MIT

oraclaw-bandit

02

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

A/B testing and feature optimization for AI agents. Pick the best option automatically using Multi-Armed Bandits and Contextual Bandits (LinUCB). No data warehouse needed — works from request.

not rated 13 2d ago A SkillSpector: pass 45 tokens original MIT

oraclaw-bayesian

03

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Bayesian inference engine for AI agents. Update beliefs with new evidence. Prior + evidence = posterior. Multi-factor prediction with calibration tracking.

not rated 13 2d ago A SkillSpector: pass 34 tokens original MIT

oraclaw-calibrate

04

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Prediction quality scoring for AI agents. Brier score, log score, and multi-source convergence analysis. Know if your forecasts are accurate and if your data sources agree.

not rated 13 2d ago A SkillSpector: pass 39 tokens original MIT

oraclaw-cmaes

05

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

CMA-ES continuous optimization for AI agents. State-of-the-art derivative-free optimizer. 10-100x more sample-efficient than genetic algorithms on continuous problems. Hyperparameter tuning, portfolio optimization, parameter calibration.

not rated 13 2d ago A SkillSpector: pass 50 tokens original MIT

oraclaw-decide

06

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Decision intelligence for AI agents. Analyze options, map decision dependencies with PageRank, detect when information sources conflict, and find the choices that matter most.

not rated 13 2d ago A SkillSpector: pass 36 tokens original MIT

oraclaw-ensemble

07

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Multi-model consensus for AI agents. Combine predictions from multiple LLMs, models, or sources into a mathematically optimal consensus. Auto-weights by historical accuracy.

not rated 13 2d ago A SkillSpector: pass 39 tokens original MIT

oraclaw-evolve

08

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Genetic Algorithm optimizer for AI agents. Multi-objective Pareto optimization for portfolio weights, pricing, hyperparameters, marketing mix — any problem with multiple competing goals. Handles nonlinear search spaces that LP solvers cannot.

not rated 13 2d ago A SkillSpector: pass 49 tokens original MIT

oraclaw-forecast

09

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Time series forecasting for AI agents. ARIMA and Holt-Winters predictions with confidence intervals. Predict revenue, traffic, prices, or any sequential data. Sub-5ms inference.

not rated 13 2d ago A SkillSpector: pass 43 tokens original MIT

oraclaw-graph

10

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Network intelligence for AI agents. PageRank, community detection (Louvain), critical path, and bottleneck analysis for any graph of connected things.

not rated 13 2d ago A 36 tokens original MIT

oraclaw-pathfind

11

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

A pathfinding and task sequencing for AI agents. Find the optimal path through workflows, dependencies, and decision trees. K-shortest paths via Yen's algorithm. Cost/time/risk breakdown.

not rated 13 2d ago A SkillSpector: pass 45 tokens original MIT

oraclaw-risk

12

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Risk assessment engine for AI agents. Value at Risk (VaR), CVaR, stress testing, and multi-factor risk scoring. Monte Carlo powered. Built for trading agents, lending agents, and portfolio managers.

not rated 13 2d ago A SkillSpector: pass 48 tokens original MIT

oraclaw-simulate

13

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Monte Carlo simulation for AI agents. Run thousands of probabilistic scenarios to model risk, forecast revenue, estimate project timelines, and quantify uncertainty. Supports 6 distribution types.

not rated 13 2d ago A SkillSpector: pass 41 tokens original MIT

oraclaw-solver

14

Whatsonyourmind/oraclaw

Skill Claude CodeCodex

Industrial-grade scheduling and resource optimization for AI agents. Solve task scheduling with energy matching, budget allocation, and any LP/MIP constraint problem in milliseconds.

not rated 13 2d ago A SkillSpector: pass 36 tokens original MIT

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