claude-flow
Verified · 2 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Structured failure knowledge for AI agents — dead ends, workarounds, error chains
claude mcp add --transport http deadends-dev https://deadends.dev/mcp
A Python-packaged server for structured failure knowledge: dead ends, workaround patterns, and error chains that could help agents avoid repeating known mistakes. It is intended for agent builders and debugging-heavy workflows; the idea is promising, but the public traction signals are still minimal, so it currently looks early and should be evaluated on data quality before relying 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.
Control real Android and iOS devices with LLM agents — tap, swipe, type, automate flows.
AI Agents Framework with Self Reflection and MCP support