rememb 0.1.2

Persistent memory standard for AI agents — local, portable, zero config

rememb

Persistent memory for AI agents — local, portable, zero config.

AI agents (Windsurf, Cursor, Claude, Continue) forget everything between sessions.
rememb gives them a structured memory that lives in your project, belongs to you, and works with any agent.

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The problem

Every developer using AI agents hits this wall:

Session 1: "We're using PostgreSQL, the auth module is at src/auth/, prefer async patterns."
Session 2: Agent starts from zero. You explain everything again.
Session 3: Same thing.

Existing solutions (Mem0, Zep, Letta) require servers, API keys, cloud accounts, and framework lock-in.
You just want the agent to remember your project.

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The solution

.rememb/
  entries.json   ← structured memory (project, actions, systems, user, context)
  meta.json      ← project metadata

That's it. A JSON file in your project. Your agent reads it at the start of every session.

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Install

pip install rememb

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Quickstart

# Initialize in your project
rememb init

# Write memories
rememb write "Project uses FastAPI + PostgreSQL + async patterns" --section project
rememb write "User prefers direct answers, no filler text" --section user
rememb write "Auth module lives at src/auth/, JWT-based" --section systems

# Read everything (for the agent)
rememb read --agent

# Search semantically
rememb search "authentication"

# Get ready-to-use rules for your editor
rememb rules windsurf
rememb rules cursor
rememb rules claude
rememb rules continue
rememb rules vscode

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Agent integration

Configure once. Works forever.

Run rememb rules <editor> to get the instructions for your editor, then paste them once. From that point on, your agent automatically reads and writes memory on every session.

rememb rules windsurf   # Windsurf / Cascade
rememb rules cursor     # Cursor
rememb rules claude     # Claude Code
rememb rules continue   # Continue.dev
rememb rules vscode     # VS Code + Copilot

Editor	Where to paste
Windsurf / Cascade	.windsurfrules at project root — or Settings → Cascade → Custom Instructions
Cursor	.cursorrules at project root — or Settings → Rules for AI
Claude Code	CLAUDE.md at project root (auto-read every session)
Continue.dev	config.json → models[].systemMessage
VS Code + Copilot	.github/copilot-instructions.md at project root (auto-read by Copilot)

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Memory sections

Section	What to store
project	Tech stack, architecture, goals
actions	What was done, decisions made
systems	Services, modules, integrations
requests	User preferences, recurring asks
user	Name, style, expertise, preferences
context	Anything else relevant

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Commands

rememb init              Initialize .rememb/ in current project
rememb write <text>      Write a memory entry (--section, --tags)
rememb read              Read all entries (--section, --agent, --raw)
rememb search <query>    Semantic search (falls back to keyword)
rememb rules [editor]    Print agent rules for windsurf/cursor/claude/continue

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How search works

rememb search uses sentence-transformers for semantic similarity search locally.
No API calls. No embeddings sent to the cloud. Falls back to keyword search if the model isn't available.

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Design principles

• Local first — everything is a JSON file in your project
• Portable — copy .rememb/ and it works anywhere
• Agnostic — works with any agent that can run CLI commands
• Zero config — pip install rememb && rememb init and you're done
• No lock-in — plain JSON, read it with anything

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Roadmap

• MCP server (rememb mcp) for native IDE integration
• rememb sync — optional encrypted remote backup
• rememb export — export to Markdown, Obsidian, Notion
• VS Code / Windsurf extension

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Contributing

git clone https://github.com/LuizEduPP/rememb
cd rememb
pip install -e ".[dev]"

PRs welcome. Issues welcome. Stars welcome. 🌟

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License

MIT