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OraClaw

MIT License Tests MCP Algorithms Latency npm API Status

MCP Optimization Tools for AI Agents -- 12 tools, 19 algorithms, sub-25ms. Zero LLM cost.

Your AI agent can't do math. OraClaw gives it deterministic optimization, simulation, forecasting, and risk analysis through the Model Context Protocol. Every tool returns structured JSON, runs in under 25ms, and costs nothing to compute.


Quick Start

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "oraclaw": {
      "command": "npx",
      "args": ["-y", "@oraclaw/mcp-server"]
    }
  }
}

Then ask your agent:

"I have 3 email subject line variants. Which should I send next?"

The agent calls optimize_bandit and gets a statistically optimal selection in 0.01ms.

2. REST API (no install)

curl -X POST https://oraclaw-api.onrender.com/api/v1/optimize/bandit \
  -H 'Content-Type: application/json' \
  -d '{
    "arms": [
      {"id": "A", "name": "Option A", "pulls": 10, "totalReward": 7},
      {"id": "B", "name": "Option B", "pulls": 10, "totalReward": 5},
      {"id": "C", "name": "Option C", "pulls": 2, "totalReward": 1.8}
    ],
    "algorithm": "ucb1"
  }'

Response (<1ms):

{
  "selected": { "id": "C", "name": "Option C" },
  "score": 1.876,
  "algorithm": "ucb1",
  "exploitation": 0.9,
  "exploration": 0.976,
  "regret": 0.1
}

Free tier: 25 calls/day, no API key needed.

3. npm SDK

npm install @oraclaw/bandit
import { OraBandit } from '@oraclaw/bandit';

const client = new OraBandit({ baseUrl: 'https://oraclaw-api.onrender.com' });
const result = await client.optimize({
  arms: [
    { id: 'A', name: 'Short Subject', pulls: 500, totalReward: 175 },
    { id: 'B', name: 'Long Subject', pulls: 300, totalReward: 126 },
  ],
  algorithm: 'ucb1',
});

14 SDK packages: @oraclaw/bandit, @oraclaw/solver, @oraclaw/simulate, @oraclaw/risk, @oraclaw/forecast, @oraclaw/anomaly, @oraclaw/graph, @oraclaw/bayesian, @oraclaw/ensemble, @oraclaw/calibrate, @oraclaw/evolve, @oraclaw/pathfind, @oraclaw/cmaes, @oraclaw/decide


Why?

LLMs generate plausible text, not optimal solutions. Ask GPT to pick the best A/B test variant and it applies a heuristic that ignores the exploration-exploitation tradeoff. Ask it to solve a linear program and it hallucinates constraints. OraClaw gives your agent access to real algorithms -- bandits, solvers, forecasters, risk models -- that return mathematically correct answers in sub-millisecond time, without burning tokens on reasoning.


MCP Tool Catalog (12 tools)

Tool

What It Does

Latency

optimize_bandit

A/B test selection via UCB1, Thompson Sampling, Epsilon-Greedy

0.01ms

optimize_contextual

Context-aware personalized selection via LinUCB

0.05ms

optimize_cmaes

Black-box continuous optimization (CMA-ES)

12ms

solve_constraints

LP/MIP/QP optimization via HiGHS solver

2ms

solve_schedule

Energy-matched task scheduling

3ms

analyze_decision_graph

PageRank, Louvain communities, bottleneck detection

0.5ms

analyze_portfolio_risk

VaR and CVaR (Expected Shortfall)

<2ms

score_convergence

Multi-source agreement scoring

0.04ms

score_calibration

Brier score and log score for prediction quality

0.02ms

predict_forecast

ARIMA and Holt-Winters time series forecasting

0.08ms

detect_anomaly

Z-Score and IQR anomaly detection

0.01ms

plan_pathfind

A* pathfinding with k-shortest paths

0.1ms

14 of 17 REST endpoints respond in under 1ms. All under 25ms.


Try It Now

The API is live. No signup required.

# Bayesian inference
curl -X POST https://oraclaw-api.onrender.com/api/v1/predict/bayesian \
  -H 'Content-Type: application/json' \
  -d '{"prior": 0.3, "evidence": [{"factor": "positive_test", "weight": 0.9, "value": 0.05}]}'

# Monte Carlo simulation
curl -X POST https://oraclaw-api.onrender.com/api/v1/simulate/montecarlo \
  -H 'Content-Type: application/json' \
  -d '{"simulations": 1000, "distribution": "normal", "params": {"mean": 100, "stddev": 15}}'

# Anomaly detection
curl -X POST https://oraclaw-api.onrender.com/api/v1/detect/anomaly \
  -H 'Content-Type: application/json' \
  -d '{"data": [10, 12, 11, 13, 50, 12, 11, 10], "method": "zscore", "threshold": 2.0}'

Pricing

Tier

Calls

Price

Auth

Free

25/day

$0

None

Pay-per-call

1K/day

$0.005/call

API key

Starter

10K/mo

$9/mo

API key

Growth

100K/mo

$49/mo

API key

Scale

1M/mo

$199/mo

API key

x402 USDC: AI agents pay $0.01-$0.15 per call with USDC on Base. No subscription, no API key.


Source Code


Building with OraClaw?

We'd love to hear what you're working on. Share your use case, ask questions, or request features:



If this saved your agent from hallucinating math, star us :star:

License

MIT

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