---
title: "Memori"
type: "tool"
slug: "memorilabs-memori"
canonical_url: "https://www.graphcanon.com/tools/memorilabs-memori"
github_url: "https://github.com/MemoriLabs/Memori"
homepage_url: "https://memorilabs.ai"
stars: 15542
forks: 2779
primary_language: "Python"
license: "Other"
categories: ["ai-agents", "developer-tools"]
tags: ["enterprise-ready", "memory-management", "stateful-systems", "python-sdk", "llm-agnostic", "typescript-sdk", "agent-memory"]
updated_at: "2026-07-07T18:29:43.132879+00:00"
---

# Memori

> Memori is agent-native memory infrastructure.

A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise use without the need to replace existing data infrastructures.

## Facts

- Repository: https://github.com/MemoriLabs/Memori
- Homepage: https://memorilabs.ai
- Stars: 15,542 · Forks: 2,779 · Open issues: 21 · Watchers: 64
- Primary language: Python
- License: Other
- Last pushed: 2026-06-15T23:18:56+00:00

## Categories

- [AI Agents](/categories/ai-agents.md)
- [Developer Tools](/categories/developer-tools.md)

## Tags

enterprise-ready, memory-management, stateful-systems, python-sdk, llm-agnostic, typescript-sdk, agent-memory

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- [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019)
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## README (excerpt)

```text
<p align="center">
  <strong>Memory from what agents do, not just what they say.</strong>
</p>

<p align="center">
  <i>Memori plugs into the software and infrastructure you already use. It is LLM, datastore and framework agnostic and seamlessly integrates into the architecture you've already designed.</i>
</p>

<p align="center">
  <strong>→ <a href="https://memorilabs.ai/docs/memori-cloud/">Memori Cloud</a></strong> — Zero config. Get an API key and start building in minutes.
</p>
<p align="center">
  <a href="https://trendshift.io/repositories/15435" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15435" alt="MemoriLabs%2FMemori | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>

<p align="center">
  <a href="https://badge.fury.io/py/memori">
    <img src="https://badge.fury.io/py/memori.svg" alt="PyPI version">
  </a>
  <a href="https://www.npmjs.com/package/@memorilabs/memori">
    <img src="https://img.shields.io/npm/v/@memorilabs/memori.svg" alt="NPM version">
  </a>
  <a href="https://pepy.tech/projects/memori">
    <img src="https://static.pepy.tech/badge/memori" alt="Downloads">
  </a>
  <a href="https://opensource.org/license/apache-2-0">
    <img src="https://img.shields.io/badge/license-Apache%202.0-blue" alt="License">
  </a>
  <a href="https://discord.gg/abD4eGym6v">
    <img src="https://img.shields.io/discord/1042405378304004156?logo=discord" alt="Discord">
  </a>
</p>

<p align="center">
  <a href="https://github.com/MemoriLabs/Memori/stargazers">
    <img src="https://img.shields.io/badge/⭐%20Give%20a%20Star-Support%20the%20project-orange?style=for-the-badge" alt="Give a Star">
  </a>
</p>

<p align="center">
  <strong>Choose memory that performs</strong>
</p>





---

## Getting Started

### Installation

<details open>
<summary><b>TypeScript SDK</b></summary>

```bash
npm install @memorilabs/memori
```
</details>

<details open>
<summary><b>Python SDK</b></summary>

```bash
pip install memori
```
</details>

### Quickstart

Sign up at [app.memorilabs.ai](https://app.memorilabs.ai), get a Memori API key, and start building. Full docs: [memorilabs.ai/docs/memori-cloud/](https://memorilabs.ai/docs/memori-cloud/).

Set `MEMORI_API_KEY` and your LLM API key (e.g. `OPENAI_API_KEY`), then:

<details open>
<summary><b>TypeScript SDK</b></summary>

```typescript
import { OpenAI } from 'openai';
import { Memori } from '@memorilabs/memori';

// Requires MEMORI_API_KEY and OPENAI_API_KEY in your environment
const client = new OpenAI();
const mem = new Memori().llm
  .register(client)
  .attribution('user_123', 'support_agent');

async function main() {
  await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: 'My favorite color is blue.' }],
  });
  // Conversations are persisted and recalled automatically in the background.

  const response = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: "What's my favorite color?" }],
  });
  // Memori recalls that your favorite color is blue.
}
```
</details>

<details open>
<summary><b>Python SDK</b></summary>

```python
from memori import Memori
from openai import OpenAI

# Requires MEMORI_API_KEY and OPENAI_API_KEY in your environment
client = OpenAI()
mem = Memori().llm.register(client)

mem.attribution(entity_id="user_123", process_id="support_agent")

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "My favorite color is blue."}]
)
# Conversations are persisted and recalled automatically.

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What's my favorite color?"}]
)
# Memori recalls that your favorite color is blue.
```
</details>

## Explore the Memories

Use the [Dashboard](https://app.memorilabs.ai) — Memories, Analytics, Playground, and API Keys.

> [!TIP]
> Want to use your own databa
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/memorilabs-memori`](/api/graphcanon/tools/memorilabs-memori)
- 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/_