Encrypted memory for AI agents: the open-source tool your server can't read

Imagine an assistant that forgets who you are every time you close the chat. Annoying, right? Today's AI agents face the same problem: they process information but can't store it reliably and persistently. Adding memory transforms them from single-use tools into assistants that learn over time and interactions. Memlawb solves this with a memory layer that remembers everything without privacy compromises.

The magic is in the design: the server hosting Memlawb is completely blind to the data it stores. Everything is encrypted end-to-end before it leaves the agent's device. The server archives only ciphertext - stuff that looks random and indecipherable. Only the agent AI, with its private key, can decrypt and read its own memory. It's like owning a safe deposit box without giving the bank the combination: even the teller doesn't know what's inside.

The project was published on GitHub by Gitlawb under an open-source license, letting anyone inspect the code and verify there are no hidden backdoors. Compatibility with the MCP protocol (Model Context Protocol) means it works with most modern AI agent frameworks, not just a single proprietary ecosystem.

Self-hosting means running your own instance of Memlawb on servers you control, not delegating to a third party. You eliminate the middleman, the risk of snooping, and vendor lock-in to a service that might raise prices or vanish tomorrow. It's the difference between renting memory from someone else and building it yourself. Not trivial if you work with sensitive data or prefer not to trust big tech companies.

The alternative is using proprietary cloud services for agent memory, but there your data passes through someone else's servers, often unencrypted. Memlawb flips the paradigm entirely: the server isn't a guard watching your files, it's just a blind warehouse.