Hey Product Hunt, I m Gaurav, founder of Agent Memory System.
I built this because AI coding agents are powerful, but they still lose project context too easily. A task can start in one tool, continue in another, and suddenly the next agent has to rediscover the repo from scratch.
Agent Memory System gives every repository a durable memory layer: project structure, architecture notes, API and security context, worklogs, graph intelligence, and handoff summaries that agents can read before they start working.
It is open source, works with tools like Codex, Claude, Cursor, and Antigravity, and includes CI checks so memory stays fresh as the codebase changes.
Hey Product Hunt, I’m Gaurav, founder of Agent Memory System.
I built this because AI coding agents are powerful, but they still lose project context too easily. A task can start in one tool, continue in another, and suddenly the next agent has to rediscover the repo from scratch.
Agent Memory System gives every repository a durable memory layer: project structure, architecture notes, API and security context, worklogs, graph intelligence, and handoff summaries that agents can read before they start working.
It is open source, works with tools like Codex, Claude, Cursor, and Antigravity, and includes CI checks so memory stays fresh as the codebase changes.
I’d love feedback from developers using AI agents in real projects:
What context do your agents keep re-reading?
Where do handoffs break down?
What should memory tooling capture next?
Thanks for checking it out. Excited to hear what you think.
This is very helpful. I was looking for this kind of project. Are you planning to keep this as open source? I am going to fork after trying this.
@rivra_dev Thanks for the comment. And yes we are committed to keep this opensource. And please star us on GitHub too.
@gauravchadhry Yes, just starred. I hope you continue great job.