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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 …

DT软件开发DTAgent 能力扩展DTMCP 服务DTSkill / 插件DTClaude CodeDTCursor

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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.

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    2026年8月7日 · 1 次收录

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