> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Node SDK Quickstart

> Store and search Mem0 memories from a TypeScript or JavaScript app in minutes.

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 theme={null}
    npm install mem0ai
    ```
  </Step>

  <Step title="Initialize the client">
    ```ts theme={null}
    import { Memory } from "mem0ai/oss";

    const memory = new Memory();
    ```
  </Step>

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

    **Output**

    ```json theme={null}
    {
      "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:

```ts theme={null}
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](/open-source/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:

<Snippet file="get-help.mdx" />