Memory documentation

Your agent knows your code. It doesn’t know your product.

Memory keeps the product graph of a codebase: features with their lifecycle stage, decisions with their reasons, gotchas, and open questions — anchored to the code paths they describe. Agents query the graph on demand mid-task and keep it current as the product changes.

It exists for a specific pain. Developers who run several projects with AI coding agents come back to a repo after weeks and neither they nor the agent remembers what is shipped, what is half-done, or why anything is built the way it is. Agents re-derive code structure cheaply; they cannot re-derive intent, stage, or rationale, because that knowledge is not in the repo. Memory stores it next to the code.

Everything is local: plain files under .memory/ (JSON sidecars plus Markdown bodies), a SQLite full-text index, no embeddings, no cloud account, no model API. Memory is distributed as the npm package @aictx/memory and the Homebrew formula aictx/tap/memory, and runs through the memory CLI and optional memory-mcp server.

The loop

init once -> query on demand -> save product changes -> sync at session end

1. memory init — once per repo. Creates storage, installs a short guidance block and a generated product map into AGENTS.md/CLAUDE.md, starts the local viewer, and prints an indexing brief the coding agent follows to build the initial graph.
2. memory query "<question>" — mid-task, on demand. Returns a token-budgeted Markdown subgraph of matching memory. There is no per-task context loading.
3. memory save --stdin — after product-meaningful changes. Intent JSON in, validated graph writes out. The product map refreshes automatically.
4. memory sync — at session end. Verifies code anchors against the actual tree and reports what went stale, with a pre-filled save skeleton.
5. memory status — features by stage, open questions, stale anchors. memory status --all is the dashboard across every registered project.

First-time setup prompt

Copy this prompt into Claude Code, Codex, Cursor, or another coding agent from the project root:

Set up Memory for this repository.

Install Memory with one of:
brew install aictx/tap/memory
npm install -g @aictx/memory

Then run from the project root:
memory init

Follow the printed indexing brief: explore the repo, draft the product graph
(features with stage and anchors, decisions with their reasons, gotchas, open
questions), interview me for what the repo cannot tell you, and save it all in
one `memory save --stdin` call.

When this is done, report:
- what the product map in AGENTS.md/CLAUDE.md now shows
- what `memory status` reports
- how I can inspect the graph with `memory view`

Start here

• Getting started installs Memory, runs init, and walks through building the first product graph and the query/save/sync loop.
• Mental model explains the product graph: kinds, stages, anchors, the map as push context, query as pull, and save discipline.
• Capabilities maps the commands to the jobs they do.
• CLI guide documents every verb and flag.
• MCP guide covers the four MCP tools and when to use them.
• Agent integration gives agents the concrete workflow and safety rules.
• Reference has the exact schema, storage layout, and save input shape.

For agents

This site is also published with agent-readable documentation files:

• /llms.txt
• /llms-full.txt
• /llms-small.txt

These files provide compact public documentation for coding agents without crawling the full website navigation.

Project health

Memory is pre-1.0; breaking changes are expected across versions, and storage recovery is memory reset followed by memory init. The public repository includes contributor guidelines, a code of conduct, security reporting instructions, support paths, a public roadmap, a release policy, CI, CodeQL, OpenSSF Scorecard, and Dependabot configuration. See the repository root for the maintained community and release files.