claude-flow
Verified · 2 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Continuous behavioral drift monitoring for LLM apps — catches silent provider model updates.
claude mcp add modelwatch -- npx -y [email protected]
Targets behavioral drift monitoring for LLM applications, specifically to catch silent upstream model changes from providers. It is for teams running production LLM systems who need observability around changing model behavior over time. The use case is timely and credible, but the project still looks early from the limited adoption signals available here.
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