Hippo is a new open-source memory management tool for AI agents that uses biological principles like decay and consolidation to ensure context remains relevant and portable across platforms.

Key Points

• Hippo functions as a shared memory layer for tools including Claude Code, Cursor, Codex, and OpenClaw.
• The system uses a SQLite backbone to store memories, supporting automatic decay, retrieval-based strengthening, and reward-proportional learning.
• It features zero runtime dependencies and integrates via simple CLI commands like hippo init and hippo recall.
• Users can import existing data from ChatGPT, Cursor rules, and markdown files to eliminate vendor lock-in.
• The tool includes advanced features like conflict detection, session handoffs, and automated learning from Git commit history.
• Performance is validated through benchmarks, showing a significant reduction in agent error rates over sequential tasks.

Why it Matters

By treating memory as a dynamic system that requires maintenance rather than a static filing cabinet, Hippo solves the common problem of AI agents repeating mistakes or losing context between sessions. This approach improves developer productivity by creating a portable, self-organizing knowledge base that evolves alongside project requirements.