memory-os

Memory OS gives an AI agent long-term memory that survives across sessions, and it runs entirely on your own machine. The problem it solves is real: most agents forget everything the moment a conversation ends, so you re-explain the same context every time. This stacks seven layers of memory, from workspace files and a session database up to vector storage in Qdrant and an auto-curated wiki, then pulls the relevant pieces into the prompt before each call. MIT licensed, and it works with OpenAI, Anthropic, OpenRouter, or local Ollama.

Running it yourself means standing up Qdrant and wiring the layers in, so the ops burden is moderate, not plug-and-play. The payoff is that your agent's memory is yours: no monthly memory subscription, no data sitting in someone else's vector store. The closest hosted options, mem0, Zep, and Letta, all want a cloud account and a recurring bill. This trades that for hardware you control.

Solo builders running a persistent agent and small teams who care where their data lives are the target. If you are already invested in the Hermes Agent ecosystem this is the native memory layer; if you are not, the architecture is the draw more than a drop-in install.

The catch is that it is built around Hermes Agent. The seven-layer design is general enough to learn from, but lifting it cleanly into a different agent framework is not free. And memory systems are only as good as their retrieval: inject the wrong context and the agent confidently runs with it.