Launched this week
PMB
Stop re-explaining your project to AI coding agents
293 followers
Stop re-explaining your project to AI coding agents
293 followers
PMB gives Claude Code, Cursor, Codex and Zed persistent project memory through MCP. It stores decisions, lessons, goals, recent work, project facts and docs in one SQLite workspace on your disk. No cloud, no API keys, no LLM call on the read path. It is open source, offline-first, inspectable/exportable, with a local dashboard and honest impact tracking so you can see which memories actually help.
Love that the whole pitch is just "stop re-explaining your project" repeated like a mantra. That repetition actually sells it, because re-feeding context every session is the exact pain I feel daily with our coding agents.
PMB
@yibo_wang3 Exactly - I wanted the pitch to stay boringly specific because the pain is boringly repetitive.
It’s not “AI memory magic”. It’s just: stop teaching the same project decisions, bugs, and rules to every new agent session. That daily context tax is the whole reason PMB exists.
Love the local-first SQLite approach here; keeping project memory on-disk instead of a hosted service is a smart trust boundary, because sensitive architecture decisions and lessons learned never leave your machine.
PMB
@ilko_kacharov Exactly the intent - a deliberate trust boundary: architecture decisions and lessons never leave your machine, and secrets are redacted on write. Thanks for getting it.
github.com/oleksiijko/pmb
PMB
Why I built this: every new Claude Code / Cursor session I'd burn the first 10 minutes re-explaining the same things - which decisions we'd already made, which directions we'd tried and ruled out, why the architecture looks the way it does. The agent forgets all of it between sessions, after every model upgrade, every time I switch tools. Teaching it the same lesson for the fifth time ("we use pnpm, never npm") was the most demoralizing part of working with an AI agent.
So I made the memory live locally - one SQLite file over MCP - and fed it back automatically before the model thinks, instead of hoping it remembers to look. Now it shows up already knowing. No cloud, no API keys, and I can open the dashboard and see exactly what it remembers. That's the whole pitch.
How does this work on projects you work on together with others? Is the data stored in the git repository or only on my machine? If only on my machine, is it possible to get the memory to be used by my team as well and the other way around?
@oleksiijko - Very nice. Definitely beats managing multiple .md files locally with skill integration. Will review in more detail, but looks very promising.
PMB
@francois_marais_nz Thanks - that's exactly the itch: replacing the sprawl of hand-maintained .md files with something that captures and retrieves on its own. Enjoy the deeper look, would genuinely value your take after.
github.com/oleksiijko/pmb
PMB
@divvsaxena Fair hit - the video's weak and I know it. Redoing it properly is on the list. Appreciate the honesty, and the upvote anyway :)
Keeping agent memory in one local SQLite file is a clean approach. Re-explaining project decisions across Claude Code, Cursor, and Codex gets old fast, so shared MCP memory could make coding sessions feel much less repetitive.
PMB
@farrukh_butt1 Thanks - shared across tools is the whole point: the memory follows you from Claude Code to Cursor to Codex, so you explain a decision once, not once per tool.
github.com/oleksiijko/pmb