I've been building a fair amount of agent stuff lately and while I was using different platforms, I realized I had a pretty simple but annoying issue on my hands. Every tool has its own idea of where memory lives, so nothing lines up and there is no place that's centralized. On top of that, the things that I actually care about remembering end up in a company's cloud, unencrypted. Hence my project, Engram. It's a small daemon that runs on your machine, keeps everything in an encrypted vault (SQLCipher), and exposes one JSON API. Anything that can POST JSON can use it (Claude Code, Cursor, shell scripts, etc.). Search is FTS5 for keywords plus local embeddings via ONNX (all-MiniLM-L6-v2), so nothing leaves the machine to get embedded. There are MCP servers, a few chat bots, a Firefox extension, and an optional sync relay if you want the same vault on several machines. The relay only stores ciphertext; keys stay client side. I wrote a small benchmark harness so I could measure retrieval, and it caught a real bug on the first run. The embedder had two arguments swapped in the model forward pass, so it had been producing near-constant embeddings for a while. My team didn't notice because keyword search was carrying the recall. After the fix the harness says 40/40, with retrieval beating full-context injection until around 110 to 150 memories. I haven't proven it actually saves tokens overall yet, that's the next thing I want to find a way to make happen. Windows builds are currently unsigned (SmartScreen will complain) and the daemon is closed source for now. The storage format is open (Apache-2.0) (https://github.com/El-AI-Intelligence/engram-format), daemon as the reference implementation. Where would a local memory daemon get in your way? The thing a vector store or an MCP config doesn't fix. Genuinely curious for any thoughts or ideas here. Install is one line: curl -fsSL https://engram.ellmstack.dev/install.sh | bash (macOS/Linux), choco install engramd (Windows). Site is https://engram.ellmstack.dev   submitted by   /u/Acceptable_Leg3950 [link]   [comments]