claudiodrews/memory-os

Memory OS solves a frustration anyone who has worked with AI agents knows well: the agent forgets everything between sessions. You spend hours teaching it your preferences and projects, and the next time you open it, you're starting from scratch. This project gives the Hermes Agent a persistent, long-term memory so it can act like a colleague who was there for every previous conversation and remembers what you discussed. Under the hood, the system is built as a "7-layer memory operating system." Instead of relying on one method to remember things, it combines several approaches. It saves permanent facts about you and your work, keeps a searchable history of every conversation you have ever had, and automatically builds a wiki of concepts it learns over time. When you ask a question, it pulls exactly the right context from these different storage layers and feeds it to the AI right before it responds. The project emphasizes that it only injects the specific information needed, keeping the process efficient rather than overwhelming the AI with a firehose of background data. This is built for people who use the Hermes Agent regularly and want it to genuinely evolve over time. For example, if you are a developer using the agent to work on a long-term software project, it will remember your architecture decisions from weeks ago. If you are a founder mapping out a business, it will recall your previous reasoning and preferences without you having to re-explain your entire company every time you sit down to brainstorm. A notable tradeoff is that this project is designed entirely around local infrastructure and privacy. All of your memory data runs on your own machine, and the system works with any major AI provider, meaning you are not locked into a specific subscription or cloud service. This focus on local-first, private memory is a deliberate choice to keep your data under your control, which sets it apart from standard cloud-based memory tools.