caura-memclaw
MemClaw is an open-source, multi-tenant, multi-agent AI fleet memory system designed for agents to store what they learn, find fleet knowledge, and improve with every interaction. It transforms plain text into searchable, governed, and self-improving memory, enabling agents to learn from each other and avoid repeating mistakes.
caura-memclaw sits in the Memory & Context category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Row-level tenant isolation with PII detection and quarantine.. A representative use case is Enabling large fleets of AI agents within an enterprise to share learned knowledge under strict governance.. The listed license is Apache-2.0. GitHub stars are currently 504. Relevant tags include AI Agent Memory, Multi-Agent System.
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