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Memory engine for AI agents. Two axes: time (three-layer decay & promotion) and space (self-organizing topic tree). Important memories get promoted, noise fades, related knowledge clusters automatically.
Most agent memory is a flat store — dump everything in, keyword search to get it back. No forgetting, no organization, no lifecycle. engram-rs adds the part that makes memory actually useful: the ability to forget what doesn't matter and surface what does.
Single Rust binary, one SQLite file, zero external dependencies. No Python, no Redis, no vector DB — curl | bash and it runs. ~10 MB binary, ~100 MB RSS, single-digit ms search latency.
Works with Claude (desktop and mobile), Cursor, Windsurf, VS Code, and any MCP-compatible AI app.
Category: Developer Tools
Don't lose this
Three weeks from now, you'll want kael-bit/engram-rs again. Will you remember where to find it?
Save it to your library and the next time you need kael-bit/engram-rs, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. kael-bit/engram-rs. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from awesome:punkpeye/awesome-mcp-servers
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