mnemos

Mnemos serves as a memory operating system for agentic AI, providing persistent context across interactions. It interoperates with major agent frameworks—including Claude Code, OpenClaw, and Hermes—through MCP, an OpenAI-compatible gateway, and native /v1/* REST endpoints. Developers can let agents record, recall, and manage memory without being locked into a single framework.

Key advantages include a standardized interface that reduces integration overhead, self-hosted control over memory data, and flexible backend customization. By unifying memory operations, it helps multi-agent systems maintain coherent state over long sessions.

Limitations and risks: The project is emerging with limited documentation and community; onboarding may require solid DevOps skills. Performance depends on the chosen storage backend and deployment setup. There is no hosted version, so users must manage their own infrastructure and monitoring. Security hardening is also the user’s responsibility.

Best suited for developers and teams building complex AI agents who already operate in an MCP-centric ecosystem. It is less suitable for those seeking a fully managed, plug-and-play memory service.