Whatsonyourmind/oraclaw

Overview

Oraclaw is a deterministic decision-intelligence MCP server for AI agents. It provides 17 tools and 21 algorithms (including LinUCB, HiGHS LP/MIP, PageRank, Monte Carlo, CMA-ES, and conformal) with sub-25ms response times and zero LLM cost. It has been field-validated in over 12 open-source projects and holds an AAA rating on Glama.

Best for

Best for
Developers building deterministic, low-latency decision agents in TypeScript

Use cases

• Embedding decision-making logic into AI agents without LLM overhead
• Running optimization or ranking algorithms (e.g., PageRank, Monte Carlo) via MCP
• Building deterministic, low-latency agent workflows for production systems

Notes

Oraclaw is a deterministic decision-intelligence MCP server for AI agents. It provides 17 tools and 21 algorithms (including LinUCB, HiGHS LP/MIP, PageRank, Monte Carlo, CMA-ES, and conformal) with sub-25ms response times and zero LLM cost. It has been field-validated in over 12 open-source projects and holds an AAA rating on Glama.

8 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

• Embedding decision-making logic into AI agents without LLM overhead
• Running optimization or ranking algorithms (e.g., PageRank, Monte Carlo) via MCP
• Building deterministic, low-latency agent workflows for production systems

Pros

• Sub-25ms latency enables real-time agent decisions
• Zero LLM cost reduces operational expenses
• Broad algorithm library (21 algorithms) covers many decision-intelligence needs

Cons

• Limited to deterministic algorithms, not suitable for probabilistic or generative tasks
• Requires MCP-compatible agent infrastructure to integrate
• Small community and ecosystem relative to larger agent frameworks

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.