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@aictx/memory

v0.1.50

Published

Local-first project memory for AI coding agents.

Readme

Memory

Memory is a local wiki for AI agents. Agents load repo context, keep it current, and you review changes.

Memory is a local wiki for AI coding agents and assistants: repo context they can load before work, keep current after meaningful changes, and leave reviewable in your project. It is inspired by Andrej Karpathy's LLM Wiki pattern: durable, human-editable project knowledge that models can read before work.

Stop re-explaining the same product intent, architecture decisions, repo conventions, setup steps, and known traps every time a new AI coding session starts. Activate Memory once in a repo: it gives agents a local wiki of durable project knowledge, wires short agent guidance into the project, and loads only the pages that matter for the current task.

Use it when you want:

  • New agents to read the repo wiki instead of asking for a long briefing.
  • Durable decisions, workflows, gotchas, and source-backed summaries to survive across sessions, branches, and reviews.
  • Local files and Git review instead of hosted memory, a vector database, or another prompt you have to manually keep current.

This repository publishes the npm package @aictx/memory and the Homebrew formula aictx/tap/memory.

Memory works with Codex, Claude Code, Cursor, Cline, OpenCode, and MCP-capable clients. Use the memory CLI by default, then add the local memory-mcp server when you want routine Memory tools inside an MCP client.

Why Memory?

Memory is for the repo wiki agents actually need: durable project context that should survive between agents, sessions, branches, and reviews without making you re-teach the repo each time.

  • Why not AGENTS.md only? Agent instruction files are good operating manuals. They become too broad and static when they also try to be the whole project wiki.
  • Why not a vector DB or RAG stack? Those are useful for large retrieval systems. Memory keeps v1 project memory local, inspectable, Git-aware, and usable without embeddings, hosted infrastructure, or a model API.
  • Why not long context? Long context helps inside one session. It does not make memory reviewable, current, reusable across future sessions, or easy to clean up when facts go stale.
  • Why local files? Plain files make the wiki reviewable and portable. Memory builds on that foundation with validation, typed memory, a local index, task-focused loading, relation-aware inspection, and a save/no-save discipline.

Inspect the Memory

Memory is not just hidden context for agents. The visual memory viewer is the wiki review surface: a local place where humans can inspect the same schema, objects, facets, relations, provenance, audit advisories, and graph context agents load.

What Gets Stored

| Memory | Use it for | | --- | --- | | decision / constraint | Choices and boundaries future agents should respect. | | workflow / gotcha | Repeatable procedures and known traps. | | source | Where important project facts came from. | | synthesis | Compact summaries of product intent, architecture, feature maps, conventions, and agent guidance. | | question / fact / concept | Open scope, reusable facts, and domain ideas. |

The full object taxonomy, facets, and write contracts live in the reference docs.

Memory does not require a cloud account, embeddings, hosted sync, an external model API, or network access for core memory commands. Saved memory is active immediately after Memory validates and writes it.

How It Works

Memory workflow: load wiki context, do work, and save durable updates.

set up once -> agents load wiki context -> save durable updates

The loop is deliberately small after setup. Agents load memory before non-trivial work, use the current repo and tests as evidence, then save only knowledge that should remain in the repo wiki for future sessions, branches, and reviews.

Get Started Quickly

Memory requires Node.js >=22. The Homebrew formula installs Node through Homebrew; npm installs require a compatible Node already on PATH. Core commands run locally; no cloud account, model API, embeddings, or hosted sync are required.

# macOS/Linux with Homebrew
brew install aictx/tap/memory

# or npm
npm install -g @aictx/memory

cd path/to/your/repo
memory setup
memory load "onboard to this repository"
memory view

memory setup activates Memory in the current repo. It creates local .memory/ memory, updates the marked Memory sections in AGENTS.md and CLAUDE.md, writes conservative first-run memory, runs checks, and starts the local viewer. Use memory setup --no-view when you do not want the viewer to start, or memory setup --dry-run to preview before writing.

Memory writes local files and never commits automatically.

Ask an Agent to Activate It

Paste this into Codex, Claude Code, OpenCode, Cursor, Cline, or another CLI-capable 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:
memory setup
memory check
memory load "onboard to this repository"

When this is done, report:
- whether setup wrote memory
- whether check passed
- how I can inspect the result with `memory view` or `memory diff`

After setup, the normal agent loop is small:

memory load "<task summary>"
# do the work
memory remember --stdin
memory diff

Save only durable project knowledge. Memory is meant to keep the repo wiki current, not archive every task transcript.

What You Get

Four surfaces ship today. Each one works locally and fits normal Git review.

| Surface | What it gives agents and humans | Try | | --- | --- | --- | | One-time setup | Creates the local wiki memory and short repo guidance so future agents know when to load and save context. | memory setup | | Task-focused loading | Pulls relevant wiki context before coding, debugging, review, architecture, or onboarding work. | memory load "change auth routes" | | Visual memory viewer | Opens a local browser for the memory schema, canonical objects, facets, maintenance advisories, relation overview, provenance, and graph context. | memory view | | Save discipline | Saves only durable facts, decisions, workflows, gotchas, source records, and syntheses. | memory remember --stdin |

Works With Your Agent

| Agent or client | Fastest path | | --- | --- | | Codex | memory setup writes AGENTS.md; use the CLI loop by default. | | Claude Code | memory setup writes CLAUDE.md; use the CLI loop by default. | | OpenCode | Uses the root AGENTS.md guidance created by setup. | | Cursor | Copy integrations/cursor/memory.mdc into .cursor/rules/memory.mdc, then run setup. | | Cline | Copy integrations/cline/memory.md into .clinerules/memory.md, then run setup. | | MCP-capable clients | Start with the CLI; configure memory-mcp later when the client exposes MCP tools. |

Distribution Artifacts

The integrations/ directory includes generated skill and plugin artifacts for external agent packaging. They package the same CLI-first guidance as the setup aids and do not add MCP configuration.

Codex users can add this repo's marketplace with one command:

codex plugin marketplace add aictx/memory

Then open Codex Plugins and install Memory.

Claude Code users can add the marketplace and install the plugin from inside Claude Code:

/plugin marketplace add aictx/memory
/plugin install memory@aictx

For official listing paths and release prep, see Publishing agent plugins.

Documentation

Contribute

Memory is MIT-licensed and built in the open. Issues, docs fixes, examples, agent recipes, and pull requests are welcome.

Contribute on GitHub

Project identity

Memory by Aictx gives AI coding agents a local wiki for repo context. It stores durable project memory as reviewable local files agents can load before work and update after meaningful changes. It is distributed through the open source npm package @aictx/memory and the Homebrew formula aictx/tap/memory, then runs through the memory CLI and optional memory-mcp server.