Hi folks. This part of AI coding always felt really dumb: after working on many projects it repeats the same mistakes, uses awkward patterns or looks up stuff over and over. It just does not remember. Skills exists, but I don't like maintaining lots of markdown files. There were other solutions for this and I'm sure there are even more now, but I simply did not fancy those for one reason or another.

So I wrote my own good-enough persistent memory which easily integrates with all AI coding tools I use. Lightweight, local, 1 Go binary + 1 SQLite file. Speaks MCP + good old REST API I can curl.

After some testing I settled on BM25 lexical search with optional WordNet synonym expansions - no embeddings, no vector DB, no external API calls. A downside is English memories only, but that's OK for me.

Memory_context pulls priority-tagged memories at session start, auto-consolidation merges near-duplicates to prevent bloat. Later I added optional memory types, project scopes and hashtags.

I've been running it as my own daily driver with Claude Code and Cursor for months now and I welcome you to try it too and provide any feedback.