claude-flow
Verified · 15 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Statistical checks an agent runs before trusting an AI eval number (is #1 real, judge bias, more).
claude mcp add evalgate -- uvx eval-integrity
A small MCP server for sanity-checking AI evaluation results, with tools aimed at judge bias, ranking stability, and related statistical pitfalls. It is most useful for teams running agent or model evals who want a quick guardrail before trusting a headline score. The scope is clear and technically relevant, but with minimal visible adoption it reads as early-stage and worth validating on real workloads before depending on it.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Draw and visually collaborate with your agents on tldraw's canvas.
Codebase knowledge graph for AI agents — 159 languages, sub-ms queries, 99% fewer tokens.
Official OpenMetadata MCP: governed context and business semantics for AI assistants and agents.
AI Agents Framework with Self Reflection and MCP support
MCP server for progressive tool usage at any scale (see https://klavis.ai)