Documentation

DevMemory is a persistent memory layer for AI coding tools. It saves your project context as you work and restores it in whatever tool you switch to next.

Overview

When your AI credits run out mid-task, the next tool starts from zero — unless your context was saved before the credits died. DevMemory makes saving deterministic: it does not rely on the model remembering to call a tool.

It captures work three ways depending on the tool:

• Transcript hooks — Claude Code and Windsurf fire an OS hook that hands over a plaintext transcript; a small script POSTs each turn.
• Watch daemon — Claude Code, Cursor, Cline, Kilo and Codex persist conversations locally; devmemory start tails those stores.
• MCP + rules — in any MCP tool (Antigravity, Claude Desktop, or any of the above), just say “continue” and the agent attaches the open project and restores it via continue_here, then saves as you work. No CLI required.

Installation

Pick whichever fits your setup — none of these require you to create a virtual environment by hand.

Quick start

Get running in under a minute:

# 1 — connect DevMemory to your tool (use --tool all for every detected tool)
devmemory install --tool cursor --api-key YOUR_KEY --host https://devmemory.io

# 2 — attach the project you're working on
devmemory start

# 3 — hit a wall? open the same project in another tool and continue
devmemory continue

Get your API key from the dashboard. Point clients at your server with --host.

The attach model

Auto-save is opt-in and scoped to one project at a time. Nothing is saved until you attach — no background daemon quietly recording every repo you touch.

Two ways to attach, same result:

• In the tool — just say “continue” (or “start on this project”). The agent calls continue_here for the folder you have open, attaching that project and restoring its context. Works in any MCP-connected tool; no terminal needed.
• From a terminal — run devmemory start in the project folder. Best for the store-tailing tools, since it also launches the watch daemon.

The CLI commands:

• devmemory start — attach the current project (resolved from its git remote), restore its saved context, and begin auto-saving. Runs until you stop; long idle gaps are fine.
• devmemory continue — re-attach the active project to a new tool, restore its context there, and resume saving from that tool.
• devmemory stop — detach and stop auto-saving.
• devmemory status — show the active project, the attached tool, and the daemon state.

Prompts to paste

No commands to memorise — say one of these to your AI tool and it drives DevMemory through the MCP tools. It uses the project folder you have open, so you never name a project (except "switch"). Click to copy:

CLI commands

Supported tools

DevMemory never fakes support. Each tool is captured by a real, verified mechanism. There are four ways context gets saved:

Per-tool summary (same data drives the in-app Setup guide, which also shows exact config snippets):

MCP tools

Once connected, your AI tool can call these directly. The one you'll use most:

• continue_here — attach this project and load its context in one call, for the folder you have open. Trigger it by saying "continue", "start on this project", or "pick up where we left off". The project is picked from the open folder automatically; to target a different one, tell the agent its name.
• save_context — save a typed block (goal, decision, code, error, next_step, note).
• get_context — retrieve saved blocks for the project or session.
• generate_resume_prompt — build a "continue here" prompt tuned for a target tool.
• start_session / end_session / list_sessions_tool — manage development sessions.
• save_tasks / update_task — track a task list across tools.
• list_projects_tool — list all projects on your account.

Self-hosting

Run DevMemory entirely on your own infrastructure. SQLite for local use, PostgreSQL for production.

# start the REST API + dashboard on http://localhost:8765
devmemory --rest --host 0.0.0.0 --port 8765

Then point clients at it with --host http://your-server:8765 during devmemory install. The dashboard lives at /app; the API reference is at /api-docs.

Troubleshooting

Nothing is being saved

Auto-save is opt-in. Run devmemory start in your project first, then check devmemory status. If the daemon isn't running, start will relaunch it.

Which tools are actually captured on this machine?

Run devmemory watch --list — it reports the exact mechanism per tool and which local stores were detected.

Context isn't loading in the new tool

Make sure you run devmemory continue from the same project directory, and that the tool was connected with devmemory install.

Need the API reference? See /api-docs. Prefer the dashboard? Open the app.