agent-memory

Persistent memory for AI coding agents. Give Claude Code, OpenAI Codex, Cursor, and Agent (Cursor CLI) a memory that survives across sessions — long-term facts, daily logs, topic notes, and a scratchpad checklist, stored as plain markdown and searchable with qmd-powered semantic search.

🌐 Website & quickstart → · Install · CLI commands · How it works

Why agent-memory?

Coding agents forget everything between sessions. agent-memory gives them a durable, local-first memory so they stop re-learning your stack, your preferences, and past decisions on every run.

• 🧠 Memory that persists — decisions, preferences, and project context carry across sessions instead of starting cold.
• 📁 Plain markdown, local-first — every memory is a readable, git-friendly file on disk. No database, no cloud, no lock-in.
• 🔍 Semantic search — optional qmd integration adds keyword, semantic, and hybrid search across all memory files.
• ⚡ Automatic context injection — relevant past memories surface into each turn, no manual tool calls required.
• 🤝 One memory, every agent — the same store is shared across Claude Code, Codex, Cursor, and Agent.

Naming: agentmemory is the GitHub repo (and Homebrew tap), myagentmemory is the npm package, and agent-memory is the installed CLI binary. Also known as coding agent memory or AI coding memory.

Installation

# Homebrew (macOS)
brew tap jayzeng/agentmemory https://github.com/jayzeng/agentmemory
brew install jayzeng/agentmemory/agent-memory

# Install the CLI globally
npm install -g myagentmemory

# If you hit SSL errors due to corporate MITM/inspection, try:
# npm config set strict-ssl false

# Or build from source
bun run build:cli
# => produces dist/agent-memory

# Initialize memory directory
agent-memory init

# Install skill files for Claude Code, Codex, Cursor, and Agent
agent-memory install-skills

# Uninstall skill files
agent-memory uninstall-skills

install-skills writes a SKILL.md into each agent's config directory:

• ~/.claude/skills/agent-memory/SKILL.md — Claude Code skill
• ~/.codex/skills/agent-memory/SKILL.md — Codex skill
• ~/.cursor/skills/agent-memory/SKILL.md — Cursor skill
• ~/.agents/skills/agent-memory/SKILL.md — Agent CLI skill (Cursor)
• %USERPROFILE%\.claude\skills\agent-memory\SKILL.md — Claude Code skill (Windows)
• %USERPROFILE%\.codex\skills\agent-memory\SKILL.md — Codex skill (Windows)
• %USERPROFILE%\.cursor\skills\agent-memory\SKILL.md — Cursor skill (Windows)
• %USERPROFILE%\.agents\skills\agent-memory\SKILL.md — Agent CLI skill (Windows)

Pi users

If you're on Pi and prefer a native extension, use pi-memory (https://github.com/jayzeng/pi-memory) instead of installing this skill. The CLI + skill workflow here is the cross-platform alternative, and works fine on Pi without any extension.

Optional: Enable search with qmd

When qmd is installed, the collection is automatically set up via agent-memory init.

Note: memory_search semantic/deep modes require vector embeddings. If you see a warning like "need embeddings", run qmd embed once and retry.

If you prefer manual setup:

qmd collection add ~/.agent-memory --name agent-memory
qmd embed

Without qmd, all core tools (write/read/scratchpad) work normally. Only memory_search and selective injection require qmd.

Architecture

  ┌───────────────┐
  │  src/core.ts  │  ← all logic: paths, truncation, scratchpad,
  └───────┬───────┘     context builder, qmd, tool functions
          │
     ┌────┴─────┐
     ▼          ▼
  ┌─────────┐   ┌─────────────────────────┐
  │ src/    │   │ skills/                 │
  │ cli.ts  │   │ ├─ claude-code/SKILL.md │
  │         │   │ ├─ codex/SKILL.md       │
  │         │   │ ├─ cursor/SKILL.md      │
  │         │   │ └─ agent/SKILL.md       │
  └─────────┘   └─────────────────────────┘
   CLI binary    instruction files
  `agent-memory`  that invoke the CLI

The memory directory defaults to ~/.agent-memory/. Override with AGENT_MEMORY_DIR env var or --dir flag.

CLI Commands

Command	Purpose
agent-memory context [--no-search]	Build & print context injection string to stdout
agent-memory write --target <long_term|daily|topic> --content <text> [--mode append|overwrite] [--topic <name>] [--date YYYY-MM-DD]	Write to memory files
agent-memory read --target <long_term|scratchpad|daily|list|topic|topics> [--date YYYY-MM-DD] [--topic <name>]	Read memory files
agent-memory scratchpad <add|done|undo|clear_done|list> [--text <text>]	Manage checklist
agent-memory search --query <text> [--mode keyword|semantic|deep] [--limit N]	Search via qmd
agent-memory install-skills	Install bundled SKILL.md files into local agent directories
agent-memory uninstall-skills	Uninstall bundled SKILL.md files from local agent directories
agent-memory init	Create dirs, detect qmd, setup collection
agent-memory status	Show config, qmd status, file counts

Global flags: --dir <path> (override directory), --json (machine output)

memory_search modes

Mode	Speed	Method	Best for
keyword	~30ms	BM25	Specific terms, dates, names, #tags, [[links]]
semantic	~2s	Vector search	Related concepts, different wording
deep	~10s	Hybrid + reranking	When other modes miss

If the first search doesn't find what you need, try rephrasing or switching modes.

File layout

~/.agent-memory/
  MEMORY.md                # Curated long-term memory
  SCRATCHPAD.md            # Checklist of things to fix/remember
  daily/
    2026-02-15.md          # Daily append-only log
    2026-02-14.md
    ...
  topics/
    auth.md                # Topic/event log linked back to daily entries

Topic notes

Topic files are for event- or theme-based tracking across days. Each topic entry includes a Daily: [[YYYY-MM-DD]] backlink so you can jump from the topic to the full daily log.

agent-memory write --target topic --topic "auth" --content "JWT refresh rolled out to edge #auth"
agent-memory read --target topic --topic "auth"
agent-memory read --target topics

How it works

Context injection

Before every agent turn, the following are injected into the system prompt (in priority order):

1. Open scratchpad items (up to 2K chars)
2. Recent topic entries (up to 2K chars) — most recent topic notes with backlinks
3. Today's daily log (up to 3K chars, tail)
4. Relevant memories via qmd search (up to 2.5K chars) — searches using the user's current prompt to surface related past context
5. MEMORY.md (up to 4K chars, middle-truncated)
6. Yesterday's daily log (up to 3K chars, tail — lowest priority, trimmed first)

Total injection is capped at 16K chars. When qmd is unavailable, step 3 is skipped and the rest works as before.

For Claude Code, context is injected via the !agent-memory context --no-search`` syntax in the SKILL.md. For Codex, Cursor, and Agent, the agent runs agent-memory context at session start.

Selective injection

When qmd is available, the system automatically searches memory using the user's prompt on demand (CLI). The top 3 keyword results are injected alongside the standard context.

The search has a 3-second timeout and fails silently. If qmd is down or the query returns nothing, injection falls back to the standard behavior.

Tags and links

Use #tags and [[wiki-links]] in memory content to improve searchability:

#decision [[database-choice]] Chose PostgreSQL for all backend services.
#preference [[editor]] User prefers Neovim with LazyVim config.
#lesson [[api-versioning]] URL prefix versioning (/v1/) avoids CDN cache issues.

These are content conventions, not enforced metadata. qmd's full-text indexing makes them searchable for free.

Other behavior

• Persistence: Memory files are plain markdown on disk — readable, editable, and git-friendly.
• Tool response previews: Write/scratchpad tools return size-capped previews instead of full file contents.
• qmd auto-setup: Via agent-memory init, the collection and path contexts are created automatically.
• qmd re-indexing: After every write, a debounced qmd update runs in the background (fire-and-forget, non-blocking) unless disabled via AGENT_MEMORY_QMD_UPDATE.
• qmd embeddings: Semantic/deep search needs vector embeddings. If you see "need embeddings" warnings, run qmd embed once and retry.
• Graceful degradation: If qmd is not installed, core tools work fine. memory_search returns install instructions.

Configuration

Variable	Values	Default	Description
AGENT_MEMORY_DIR	path	~/.agent-memory	Memory directory
AGENT_MEMORY_QMD_UPDATE	background, manual, off	background	Controls automatic qmd update after writes

Running tests

# Unit tests (no LLM, no qmd — fast, deterministic)
bun test test/unit.test.ts
bun test test/cli.test.ts

Test levels

Level	File	Requirements	What it tests
Unit	test/unit.test.ts	None	Utilities, scratchpad parsing, context builder, qmd helpers, tool functions
CLI	test/cli.test.ts	None	CLI commands, subprocess integration

Development

# Build the CLI binary
bun run build:cli

# Test CLI
agent-memory write --target long_term --content "test" && agent-memory read --target long_term

# Install skills
agent-memory install-skills

Publishing (maintainers)

# Confirm package name is available
npm view myagentmemory

# Bump version (choose patch/minor/major)
npm version patch

# Publish to npm (public)
npm publish --access public

Repository assets (maintainers)

• Social preview image: .github/assets/social-preview.png (1280×640)
• Release notes template: .github/release.yml (used by GitHub auto-generated release notes)
• Landing page source: docs/index.html (deployed by .github/workflows/deploy-pages.yml)

Acknowledgments

Inspired by skyfallsin/pi-mem. Semantic search is powered by qmd.

Changelog

0.4.12

• Removed pi extension: Removed index.ts and all pi-specific code (@mariozechner/pi-ai, @mariozechner/pi-coding-agent, @sinclair/typebox peer dependencies).
• Standalone tool functions: Extracted memoryWrite(), memoryRead(), scratchpadAction(), memorySearch() into src/core.ts as standalone functions usable without any framework.
• Renamed package: pi-memory → myagentmemory (npm); the CLI binary is agent-memory.
• Renamed env var: PI_MEMORY_QMD_UPDATE → AGENT_MEMORY_QMD_UPDATE (old name still works as fallback).
• Default memory directory: Now always ~/.agent-memory/.
• Removed pi-specific tests: Deleted test/e2e.ts, test/eval-recall.ts, test/unit.ts.

0.4.0

• Multi-platform support: Memory system now works with Claude Code and OpenAI Codex via CLI + skills, in addition to pi.
• Extracted shared core: src/core.ts contains platform-agnostic logic (paths, truncation, scratchpad, context builder, qmd) with zero pi peer dependencies.
• CLI binary: agent-memory CLI with subcommands: context, write, read, scratchpad, search, init, status.
• Skill files: skills/claude-code/SKILL.md and skills/codex/SKILL.md for installation into respective platforms.
• Configurable memory directory: AGENT_MEMORY_DIR env var or --dir flag (default: ~/.agent-memory/).
• CLI tests: test/cli.test.ts with unit and subprocess tests.

0.2.0

• Selective injection: Before each turn, the user's prompt is searched against memory via qmd. Top results are injected into the system prompt alongside standard context, surfacing relevant past decisions without explicit tool calls.
• qmd auto-setup: The extension automatically creates the collection and path contexts on session start when qmd is available. No manual qmd collection add needed.
• Tags and links: memory_write and context injection now encourage #tags and [[wiki-links]] as searchable content conventions.
• Context priority reordering: Injection order is now scratchpad > today > search results > MEMORY.md > yesterday.
• Unit tests: Added deterministic tests (no LLM/qmd needed).
• Recall eval: Added recall effectiveness evaluation.

0.1.0

• Initial release: memory_write, memory_read, scratchpad, memory_search tools.
• Context injection of MEMORY.md, scratchpad, and today/yesterday daily logs.
• qmd integration for keyword, semantic, and hybrid search.
• Debounced background qmd update after writes.