Node SDK Quickstart - Mem0

Spin up Mem0 with the Node SDK in just a few steps. You'll install the package, initialize the client, add a memory, and confirm retrieval with a single search.

Prerequisites

Node.js 18 or higher
(Optional) OpenAI API key stored in your environment when you want to customize providers

Install and run your first memory

<Steps> <Step title="Install the SDK"> ```bash npm install mem0ai ``` </Step> <Step title="Initialize the client"> ```ts import { Memory } from "mem0ai/oss";

const memory = new Memory();

</Step>

<Step title="Add a memory">
```ts
const messages = [
  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." }
];

await memory.add(messages, { userId: "alice", metadata: { category: "movie_recommendations" } });

</Step> <Step title="Search memories"> ```ts const results = await memory.search("What do you know about me?", { filters: { userId: "alice" } }); console.log(results); ```

Output

json

{
  "results": [
    {
      "id": "892db2ae-06d9-49e5-8b3e-585ef9b85b8e",
      "memory": "User is planning to watch a movie tonight.",
      "score": 0.38920719231944799,
      "metadata": {
        "category": "movie_recommendations"
      },
      "userId": "alice"
    }
  ]
}

</Step> </Steps> <Snippet file="star-on-github.mdx" /> <Note> By default the Node SDK uses local-friendly settings (OpenAI `gpt-5-mini`, `text-embedding-3-small`, in-memory vector store, and SQLite history). Pass a config to swap any of them. </Note>

Configure providers

Pass a config object to new Memory() to use your own LLM, embedder, and vector store:

import { Memory } from "mem0ai/oss";

const memory = new Memory({
  llm: {
    provider: "openai",
    config: { apiKey: process.env.OPENAI_API_KEY || "", model: "gpt-4-turbo-preview" }
  },
  embedder: {
    provider: "openai",
    config: { apiKey: process.env.OPENAI_API_KEY || "", model: "text-embedding-3-small" }
  },
  vectorStore: {
    provider: "memory",
    config: { collectionName: "memories", dimension: 1536 }
  }
});

For the full provider catalog, history stores, and every config option, see Configuration.

What's next?

<CardGroup cols={3}> <Card title="Memory operations" icon="database" href="/core-concepts/memory-operations/add"> Search, update, and manage memories with the full CRUD API. </Card> <Card title="Configure for production" icon="sliders" href="/open-source/configuration"> Swap in your own LLM, embedder, and vector store. </Card> <Card title="Add to your framework" icon="plug" href="/integrations"> Wire Mem0 into LangChain, CrewAI, LangGraph, and 20+ more. </Card> </CardGroup>

If you have any questions, please feel free to reach out: