📚 Hippo Memory: Biologically-Inspired Agent Memory

The approach here is quite interesting. Instead of building a traditional database, Hippo Memory mimics biological brain mechanisms for AI agents. It introduces concepts like memory decay, retrieval strengthening, and consolidation. Technically, it is very lean: zero runtime dependencies, backed by SQLite, and natively supports the Model Context Protocol (MCP). This makes it easy to plug into existing agent workflows. It is less about building a massive knowledge base and more about exploring how to make AI memory behave like human memory—strengthening frequently accessed information and letting unused data decay. For developers researching long-term memory and context management in agents, this biologically-inspired, lightweight solution offers a fresh perspective.