Your AI credits run out mid-task. You jump to another tool — and start from zero. DevMemory saves your goals, decisions and code as you work, then restores them in the next tool. Deterministically.
Free tier included · Self-hostable · No vendor lock-in
One memory layer for the tools you already use
Saving your work can't depend on the model remembering to do it. So it doesn't.
Saves each turn through OS-level hooks and a watch daemon — with zero reliance on the AI calling a tool. Your work is captured before the credits die.
One devmemory continue in a new tool restores your goals, decisions and next steps — a resume prompt tuned for that tool. No copy-paste.
Not a transcript dump. Typed blocks — goals, decisions, code, errors, next steps — so the next session reads intent, not noise.
Auto-save is scoped to the one project you attach with devmemory start. Nothing saved until you say so — you're always in control.
Run it locally on SQLite or scale on PostgreSQL. Your context stays on your infrastructure. No lock-in, MIT-licensed.
We never fake support. devmemory watch --list shows the exact save mechanism per tool — hook, daemon, or MCP+rules.
One command wires DevMemory into your tool via MCP + hooks. Python or Node — your choice.
Run devmemory start in your project. It attaches, restores context, and auto-saves as you work.
Hit a wall in one tool? devmemory continue in the next — your context follows you.
Set up DevMemory in under a minute and keep your context — across every switch, every credit reset.