claude-flow
Verified · 2 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.
claude mcp add supermemory -- uvx supermemory-agent
This project is positioned as an MCP-first memory and learning layer for agents, focused on storing failures, validating lessons, and retrieving context later. It is for agent developers experimenting with iterative improvement and long-lived context rather than users looking for a simple connector. The concept is interesting, but the description is abstract enough that implementation quality and actual learning rigor would need careful inspection.
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