tstockham

https://github.com/tstockham96/engram

About two weeks ago, I posted Engram here, a memory layer for AI agents. The response was great and pushed me to keep building. Here's where things stand.What changed since the last post:DMR benchmark: 92.0% accuracy (460/500). Retrieval hit rate is 96.4%. This is competitive with systems backed by graph databases and Python ML stacks. Engram is TypeScript + SQLite.LOCOMO benchmark...

https://www.engram.fyi

Engram gives AI coding agents persistent memory across sessions. 2,500 npm installs in the first five days. The problem: every Claude Code or Cursor session starts from zero. You re-explain your architecture, conventions, past decisions. CLAUDE.md helps but it's manual and doesn't scale. Engram runs as a native MCP server. One command to install, SQLite backend, no infrastructure. Three tiers...

https://www.engram.fyi/

I built Engram because every AI agent I worked with forgot everything between sessions. Existing solutions (Mem0, Zep) are Python-first and extraction-based. They aggressively compress conversations into facts at write time.Engram takes the opposite approach: store memories with rich metadata and invest intelligence at read time, when you actually know the query. TypeScript, SQLite, zero...

https://github.com/tstockham96/engram

I built Engram because my AI coding agent (Claude Code) has no memory between sessions. Every new session starts from zero. I kept re-explaining the same project context, decisions, and preferences.Engram is a persistent memory system designed for AI agents. It runs as an MCP server alongside Claude Code, Cursor, or any MCP-compatible client. One command to set up:``` npm install -g...