If you've ever used an AI coding tool — Claude Code, Cursor, or similar — you've noticed something quietly maddening: every single session starts from zero. You explain your project again. You mention the same quirks again. You remind it of the decision you made three weeks ago about how to handle customer emails. Again.
It's like hiring a brilliant contractor who shows up every morning with no memory of yesterday.
This open-source tool sits quietly in the background and watches what happens during each session. It takes notes — on decisions made, bugs found, preferences you've shown — and compresses them into something searchable. When you start a new session, it slips the relevant context in automatically, without you having to say a word.
One memory store, shared across whichever AI tools you use. Runs entirely on your own computer. No third-party service gets your data. No monthly fee.
It's currently ranked first in independent benchmarks for this kind of tool, ahead of several well-funded alternatives.
The less time your team spends re-explaining context to AI tools, the more useful those tools actually become. This is especially true if you're working on something with real complexity — a product, a client platform, a custom system that has its own logic and history.
AI coding agent — an AI assistant (like Claude or Cursor) that can write, read, and edit code on your behalf, almost like a junior developer.
Context — everything an AI needs to know about your project to give useful answers. The more it has, the better it performs.
Self-hosted — running software on your own machine or server, rather than someone else's cloud. Your data stays with you.
Open-source — the code is publicly available. Anyone can inspect it, use it, or improve it.
If you work with developers who use AI tools daily, it's worth asking them: how much time do we spend re-teaching the same things? That number might surprise you.