Stop re-explaining your project to AI coding agents
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.
Hi Product Hunt - I built PMB because every coding agent I used had the same frustrating loop: brilliant in one session, forgetful in the next. I kept re-explaining decisions, constraints, file history, and "please never do X in this repo again."
PMB makes that memory local and durable. It stores decisions, lessons, goals, recent work and facts in one SQLite workspace on your disk, then feeds the relevant context back to Claude Code, Cursor, Codex, Zed and other MCP-aware agents. No cloud, no API keys, no hosted memory service.
The design evolved from "just save notes for the agent" into typed memory: lessons are treated as rules, goals as goals, and project work as recent activity. The thing I care about most now is trustworthy memory: what should an agent remember automatically, what should it ignore, and how do we show when memory is actually helping?
Would love feedback from people using coding agents every day. Fastest try: pip install pmb-ai && pmb setup
About PMB on Product Hunt
“Stop re-explaining your project to AI coding agents”
PMB launched on Product Hunt on June 29th, 2026 and earned 175 upvotes and 46 comments, placing #5 on the daily leaderboard. 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.
On the analytics side, PMB competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how PMB performed against the three products that launched closest to it on the same day.
Who hunted PMB?
PMB was hunted by Oleksii Bondar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of PMB including community comment highlights and product details, visit the product overview.
Oleksii Bondar