---
title: "OpenMemory"
type: "tool"
slug: "caviraoss-openmemory"
canonical_url: "https://www.graphcanon.com/tools/caviraoss-openmemory"
github_url: "https://github.com/CaviraOSS/OpenMemory"
homepage_url: "https://openmemory.cavira.app"
stars: 4314
forks: 488
primary_language: "TypeScript"
license: "Apache-2.0"
categories: ["evaluation-observability", "llm-frameworks"]
tags: ["self-hosted", "memory-retrieval", "long-term-memory", "ai-agents"]
updated_at: "2026-07-07T18:41:15.20067+00:00"
---

# OpenMemory

> Local persistent memory store for LLM applications

OpenMemory is a cognitive memory engine designed to provide real long-term memory functionality for AI agents and language models. It supports multiple database backends (SQLite, PostgreSQL) and provides Python and Node SDKs with extensive integrations.

## Facts

- Repository: https://github.com/CaviraOSS/OpenMemory
- Homepage: https://openmemory.cavira.app
- Stars: 4,314 · Forks: 488 · Open issues: 13 · Watchers: 34
- Primary language: TypeScript
- License: Apache-2.0
- Last pushed: 2026-06-27T05:17:02+00:00

## Categories

- [Evaluation & Observability](/categories/evaluation-observability.md)
- [LLM Frameworks](/categories/llm-frameworks.md)

## Tags

self-hosted, memory-retrieval, long-term-memory, ai-agents

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## README (excerpt)

```text
# 🚧 This project is currently being rewritten.

Expect breaking changes and potential bugs.
### Contributers needed
To contribute, visit https://github.com/CaviraOSS/OpenMemory/tree/rewrite branch.
If you find an issue, please open a GitHub issue with details so it can be tracked and resolved.
## OpenMemory

> **Real long-term memory for AI agents. Not RAG. Not a vector DB. Self-hosted, Python + Node.**









OpenMemory is a **cognitive memory engine** for LLMs and agents.

- 🧠 Real long-term memory (not just embeddings in a table)
- 💾 Self-hosted, local-first (SQLite / Postgres)
- 🐍 Python + 🟦 Node SDKs
- 🧩 Integrations: LangChain, CrewAI, AutoGen, Streamlit, MCP, VS Code
- 📥 Sources: GitHub, Notion, Google Drive, OneDrive, Web Crawler
- 🔍 Explainable traces (see *why* something was recalled)

Your model stays stateless. **Your app stops being amnesiac.**

---

## 1. TL;DR – Use It in 10 Seconds

### 🐍 Python (local-first)

Install:

```bash
pip install openmemory-py
```

Use:

```python
from openmemory.client import Memory

mem = Memory()
mem.add("user prefers dark mode", user_id="u1")
results = mem.search("preferences", user_id="u1")
await mem.delete("memory_id")
```

> Note: `add`, `search`, `get`, `delete` are async. Use `await` in async contexts.

#### 🔗 OpenAI

```python
mem = Memory()
client = mem.openai.register(OpenAI(), user_id="u1")
resp = client.chat.completions.create(...)
```

#### 🧱 LangChain

```python
from openmemory.integrations.langchain import OpenMemoryChatMessageHistory

history = OpenMemoryChatMessageHistory(memory=mem, user_id="u1")
```

#### 🤝 CrewAI / AutoGen / Streamlit

OpenMemory is designed to sit behind **agent frameworks and UIs**:

- Crew-style agents: use `Memory` as a shared long-term store
- AutoGen-style orchestrations: store dialog + tool calls as episodic memory
- Streamlit apps: give each user a persistent memory by `user_id`

See the integrations section in the docs for concrete patterns.

---

### 🟦 Node / JavaScript (local-first)

Install:

```bash
npm install openmemory-js
```

Use:

```ts
import { Memory } from "openmemory-js"

const mem = new Memory()
await mem.add("user likes spicy food", { user_id: "u1" })
const results = await mem.search("food?", { user_id: "u1" })
await mem.delete("memory_id")
```

Drop this into:

- Node backends
- CLIs
- local tools
- anything that needs durable memory without running a separate service.

---

### 📥 Connectors

Ingest data from external sources directly into memory:

```python
# python
github = mem.source("github")
await github.connect(token="ghp_...")
await github.ingest_all(repo="owner/repo")
```

```ts
// javascript
const github = await mem.source("github")
await github.connect({ token: "ghp_..." })
await github.ingest_all({ repo: "owner/repo" })
```

Available connectors: `github`, `notion`, `google_drive`, `google_sheets`, `google_slides`, `onedrive`, `web_crawler`

---

## 2. Modes: SDKs, Server, MCP

OpenMemory can run **inside your app** or as a **central service**.

### 2.1 Python SDK

- ✅ Local SQLite by default
- ✅ Supports external DBs (via config)
- ✅ Great fit for LangChain / LangGraph / CrewAI / notebooks

Docs: https://openmemory.cavira.app/docs/sdks/python

---

### 2.2 Node SDK

- Same cognitive model as Python
- Ideal for JS/TS applications
- Can either run fully local or talk to a central backend

Docs: https://openmemory.cavira.app/docs/sdks/javascript

---

### 2.3 Backend server (multi-user + dashboard + MCP)

Use when you want:

- org‑wide memory
- HTTP API
- dashboard
- MCP server for Claude / Cursor / Windsurf

Run from source:

```bash
git clone https://github.com/CaviraOSS/OpenMemory.git
cd OpenMemory
cp .env.example .env

cd packages/openmemory-js
npm install
npm run dev   # default :8080
```

Or with Docker (API + MCP):

```bash
docker compose up --build -d
```

Optional: include the dashboard service profile:

```bash
docker compose --profile ui up --build -d
```

Using Doppler-managed config (
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/caviraoss-openmemory`](/api/graphcanon/tools/caviraoss-openmemory)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_