📚 Caura-memclaw: Governed Memory for Agent Fleets

The direction here is highly relevant right now: as multiple AI agents begin to collaborate, they require a shared, governed memory system. Caura-memclaw explores memory management for multi-agent and multi-tenant fleets, built with native support for the Model Context Protocol (MCP). This is not just a vector database wrapper; it acts more like a governed memory hub for agent fleets. By integrating knowledge graphs, trust tiers, and audit trails, it tackles the challenges of data isolation and retrieval in complex agent interactions. For enterprise scenarios where agent orchestration requires strict policy controls and verifiable memory access, this infrastructure approach is quite compelling.