Hey r/GoodOpenSource!

A few months ago, I shared Mind here. The feedback was great, particularly the questions about memory aging, local storage, and how an agent decides what to remember.

Today I'm releasing Mind v1.7.0, probably the biggest update to the project so far.

Mind is an open-source, MIT-licensed persistent memory layer for AI coding agents. It preserves decisions, project knowledge, checkpoints, and useful discoveries across sessions, context compaction, and different development tools.

What's new?

• 86.67% answer accuracy on a 120-question stratified OmniMemEval LongMemEval-S run, without embeddings. By raw score, that's in the territory of the top published results, although it isn't an official or directly equivalent leaderboard comparison.
• Much stronger local search, combining FTS5, phrase matching, substring matching, typo tolerance, and optional semantic retrieval.
• A redesigned web application, including Neural Map, search, filtering, and memory inspection.
• More reliable session continuity, with atomic checkpoint completion and preserved memory relationships.
• Simpler agent integration, with a shared management skill and support for OpenCode, Claude Code, Codex, Cursor, and more.

Everything is built with Bun, TypeScript, and SQLite. Core memory and retrieval work locally without an embedding API.

This isn't meant to be another code indexer or vector database wrapper. It's a structured memory lifecycle for agents: remember, retrieve, relate, update, and eventually supersede outdated knowledge.

The implementation, tests, and benchmark methodology are public.

GitHub: https://github.com/GabrielMartinMoran/mind

v1.7.0 release: https://github.com/GabrielMartinMoran/mind/releases/tag/v1.7.0

If you find the project interesting, a GitHub star helps more people discover it.

I'd especially appreciate feedback on the retrieval architecture, memory lifecycle, and agent integrations. Contributions are welcome!