GitHub - SMJAI/open-memory-protocol: An open standard for portable, interoperable AI memory across tools, sessions, and devices.

An open standard for portable, interoperable AI memory across tools, sessions, and devices.

The Problem Every AI tool remembers you differently — and only within its own walls.

Claude knows what you told it yesterday. Cursor doesn't. ChatGPT learned your preferences. Your custom agent hasn't. Copilot saw your code style. Your terminal AI is starting from zero.

Every time you switch tools, your AI forgets you. You repeat yourself. Context is lost. The AI that was finally starting to know you resets to a stranger. This is the AI memory silo problem. And it has the same solution as every silo problem before it: an open protocol.

What is OMP? Open Memory Protocol is a vendor-neutral specification for how AI tools store, retrieve, and share memory about users and their context. It is:

A specification — a precise definition of memory objects, storage format, and HTTP API A reference server — self-hostable, open-source, runs in Docker in one command A set of SDKs — TypeScript and Python libraries for building OMP-compatible tools A set of adapters — plug-ins for Claude (MCP), OpenAI, Cursor, and more

Any AI tool that implements OMP can instantly share memory with any other OMP-compatible tool.

Quick Start

Requirements: Node.js 22 or newer

1. Run your memory server npx omp-server Or with Docker: docker run -p 3456:3456 -v omp-data:/data ghcr.io/smjai/omp-server Your server is now running at http://localhost:3456. Test it: curl http://localhost:3456/v1/health # {"status":"ok","version":"0.1","compliance":"OMP-Core","memories_count":0} 2.

Connect Claude (via MCP) Add to your Claude Desktop config (~/.claude/claude_desktop_config.json): { "mcpServers": { "omp": { "command": "npx", "args": ["omp-mcp"], "env": { "OMP_SERVER": "http://localhost:3456", "OMP_API_KEY": "your-omp-key" } } } } To enable AI-powered memory extraction and compression, also set these on the server: OMP_AI_PROVIDER=anthropic # or "openai" OMP_AI_API_KEY=sk-ant-... # your Anthropic or OpenAI key Write a memory from any tool curl -X POST http://localhost:3456/v1/memories \ -H "Content-Type: application/json" \ -d '{ "content": "User prefers TypeScript over JavaScript and dislikes verbose comments", "type": "semantic", "source": { "tool": "claude" }, "tags": ["preferences", "coding"] }' Query from any other tool curl "http://localhost:3456/v1/memories/search?q=coding+preferences"

How It Works ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ Claude │ │ Cursor │ │ Your Agent │ │ (MCP) │ │ (SDK) │ │ (REST API) │ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │ │ │ └───────────────────┼───────────────────┘ │

┌────────▼────────┐ │ OMP Server │ │ (self-hosted) │ │ │ │ ┌───────────┐ │ │ │ SQLite │ │ │ │ / Pgvec │ │ │ └───────────┘ │ └─────────────────┘

Every tool reads and writes to a single OMP server you control. One memory store. All tools. Zero silos.

The Spec OMP defines:

Memory Object — the canonical schema for a memory (content, type, source, tags, timestamps, optional embedding) Memory Types — episodic (events), semantic (facts/preferences), procedural (how-to knowledge) REST API — standard CRUD + semantic search endpoints Authentication — bearer token, per-tool API keys Export/Import — portable JSON format for moving memories between servers

Read the full specification: SPEC.md

Memory Object { "id": "mem_01j9xk2p3q4r5s6t", "content": "User is building a fintech startup, prefers clean architecture, dislikes over-engineering", "type": "semantic", "source": { "tool": "claude", "session_id": "sess_abc123", "timestamp": "2026-06-29T12:00:00Z" }, "tags": ["profile", "preferences", "engineering"], "created_at": "2026-06-29T12:00:00Z", "updated_at": "2026-06-29T12:00:00Z", "expires_at": null }

Adapters

Tool Status Install

Claude (MCP) ✅ Available npx omp-mcp

OpenAI Assistants 🙋 Help wanted Open issue

Cursor 🙋 Help wanted Open issue

Copilot / VS Code 🙋 Help wanted Open issue

Gemini 🙋 Help wanted Open issue

Custom (REST) ✅ Available Any HTTP client

Want to build one? An adapter is typically 100–200 lines — read CONTRIBUTING.md and use adapters/claude-mcp as a template.

SDKs The OMP API is plain REST — any HTTP client works out of the box. Typed SDKs are on the roadmap. Want to build one? Python, Go, Rust, and Ruby SDKs are all needed. See CONTRIBUTING.md. REST (any language) # Save a memory curl -X POST http://localhost:3456/v1/memories \ -H "Content-Type: application/json" \ -d '{"content":"User prefers TypeScript","type":"semantic","source":{"tool":"myapp","timestamp":"2026-06-30T00:00:00Z"}}'

# Search memories curl -X POST http://localhost:3456/v1/memories/search \ -H "Content-Type: application/json" \ -d '{"q":"TypeScript","limit":5}'

Why Open Source? Your memories are yours. They should not be locked inside a company's database, used to train models without your consent, or lost when you switch tools. OMP is designed on these principles:

Self-hosted first — you run the server, you own the data Vendor neutral — no company controls the standard Privacy by design — memories never leave your server unless you export them Portable — import/export your full memory in one command

Roadmap

v0.1 — Core spec, reference server, MCP

adapter v0.2 — AI memory extraction, conversation compression, MCP resources + prompts v0.3 — Semantic search with embeddings, pgvector support v0.4 — Memory namespacing (per-project memories) v0.5 — Multi-user support, access control v1.0 — Stable spec, submitted to open standards body

Contributing OMP is community-driven. We need:

Adapter builders — connect your favourite AI tool SDK contributors — Go, Rust, Java SDKs welcome Spec reviewers — read SPEC.md and open issues Early adopters — try it and report what breaks

See CONTRIBUTING.md to get started.

Community

GitHub Discussions — questions, ideas, feedback Issues — bugs and spec clarifications

License Apache 2.0 — free to use, modify, and distribute. See LICENSE. Built by SMJAI and contributors.