claude-flow
Verified · 2 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Universal governance layer for AI agents. MCP-native, fail-closed, audit proofs and rollback.
claude mcp add dingdawg-governance -- npx -y [email protected]
A governance and control layer for AI agents, with emphasis on fail-closed behavior, audit proofs, and rollback. It is for teams building agent systems that need policy enforcement and operational guardrails more than end-user features. The positioning is ambitious, but the very small adoption footprint means the claims should be validated carefully before relying on it in production.
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