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@@ -4,7 +4,7 @@ description: "Store and search Mem0 memories from a TypeScript or JavaScript app
icon: "js"
---
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.
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
@@ -67,218 +67,45 @@ console.log(results);
</Steps>
<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). Swap components by passing a config as shown below.
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 for production
## Configure providers
Pass a config object to `new Memory()` to use your own LLM, embedder, and vector store:
```ts
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"
}
config: { apiKey: process.env.OPENAI_API_KEY || "", model: "text-embedding-3-small" }
},
vectorStore: {
provider: "memory",
config: {
collectionName: "memories",
dimension: 1536
}
},
llm: {
provider: "openai",
config: {
apiKey: process.env.OPENAI_API_KEY || "",
model: "gpt-4-turbo-preview"
}
},
historyDbPath: "memory.db"
});
```
## Manage memories (optional)
<CodeGroup>
```ts Get all memories
const allMemories = await memory.getAll({ filters: { userId: "alice" } });
console.log(allMemories);
```
```ts Get one memory
const singleMemory = await memory.get("892db2ae-06d9-49e5-8b3e-585ef9b85b8e");
console.log(singleMemory);
```
```ts Search memories
const result = await memory.search("What do you know about me?", { filters: { userId: "alice" } });
console.log(result);
```
```ts Update a memory
const updateResult = await memory.update(
"892db2ae-06d9-49e5-8b3e-585ef9b85b8e",
"I love India, it is my favorite country."
);
console.log(updateResult);
```
</CodeGroup>
```ts
// Audit history
const history = await memory.history("892db2ae-06d9-49e5-8b3e-585ef9b85b8e");
console.log(history);
// Delete specific or scoped memories
await memory.delete("892db2ae-06d9-49e5-8b3e-585ef9b85b8e");
await memory.deleteAll({ userId: "alice" });
// Reset everything
await memory.reset();
```
## Use a custom history store
The Node SDK supports Supabase (or other providers) when you need serverless-friendly history storage.
<CodeGroup>
```ts Supabase provider
import { Memory } from "mem0ai/oss";
const memory = new Memory({
historyStore: {
provider: "supabase",
config: {
supabaseUrl: process.env.SUPABASE_URL || "",
supabaseKey: process.env.SUPABASE_KEY || "",
tableName: "memory_history"
}
config: { collectionName: "memories", dimension: 1536 }
}
});
```
```ts Disable history
import { Memory } from "mem0ai/oss";
const memory = new Memory({
disableHistory: true
});
```
</CodeGroup>
Create the Supabase table with:
```sql
create table memory_history (
id text primary key,
memory_id text not null,
previous_value text,
new_value text,
action text not null,
created_at timestamp with time zone default timezone('utc', now()),
updated_at timestamp with time zone,
is_deleted integer default 0
);
```
## Configuration parameters
Mem0 offers granular configuration across vector stores, LLMs, embedders, and history stores.
<AccordionGroup>
<Accordion title="Vector store">
| Parameter | Description | Default |
| --- | --- | --- |
| `provider` | Vector store provider (e.g., `"memory"`) | `"memory"` |
| `host` | Host address | `"localhost"` |
| `port` | Port number | `undefined` |
</Accordion>
<Accordion title="LLM">
| Parameter | Description | Provider |
| --- | --- | --- |
| `provider` | LLM provider (e.g., `"openai"`, `"anthropic"`) | All |
| `model` | Model to use | All |
| `temperature` | Temperature value | All |
| `apiKey` | API key | All |
| `maxTokens` | Max tokens to generate | All |
| `topP` | Probability threshold | All |
| `topK` | Token count to keep | All |
| `openaiBaseUrl` | Base URL override | OpenAI |
</Accordion>
<Accordion title="Embedder">
| Parameter | Description | Default |
| --- | --- | --- |
| `provider` | Embedding provider | `"openai"` |
| `model` | Embedding model | `"text-embedding-3-small"` |
| `apiKey` | API key | `undefined` |
</Accordion>
<Accordion title="General">
| Parameter | Description | Default |
| --- | --- | --- |
| `historyDbPath` | Path to history database | `"{mem0_dir}/history.db"` |
| `customInstructions` | Custom processing prompt | `undefined` |
</Accordion>
<Accordion title="History store">
| Parameter | Description | Default |
| --- | --- | --- |
| `provider` | History provider | `"sqlite"` |
| `config` | Provider configuration | `undefined` |
| `disableHistory` | Disable history store | `false` |
</Accordion>
<Accordion title="Complete config example">
```ts
const config = {
embedder: {
provider: "openai",
config: {
apiKey: process.env.OPENAI_API_KEY || "",
model: "text-embedding-3-small"
}
},
vectorStore: {
provider: "memory",
config: {
collectionName: "memories",
dimension: 1536
}
},
llm: {
provider: "openai",
config: {
apiKey: process.env.OPENAI_API_KEY || "",
model: "gpt-4-turbo-preview"
}
},
historyStore: {
provider: "supabase",
config: {
supabaseUrl: process.env.SUPABASE_URL || "",
supabaseKey: process.env.SUPABASE_KEY || "",
tableName: "memories"
}
},
disableHistory: false,
customInstructions: "I'm a virtual assistant. I'm here to help you with your queries."
};
```
</Accordion>
</AccordionGroup>
For the full provider catalog, history stores, and every config option, see [Configuration](/open-source/configuration).
## What's next?
<CardGroup cols={3}>
<Card title="Explore Memory Operations" icon="database" href="/core-concepts/memory-operations/add">
Review CRUD patterns, filters, and advanced retrieval across the OSS stack.
<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="Customize Configuration" icon="sliders" href="/open-source/configuration">
Swap in your preferred LLM, vector store, and history provider for production use.
<Card title="Configure for production" icon="sliders" href="/open-source/configuration">
Swap in your own LLM, embedder, and vector store.
</Card>
<Card title="Automate Node Workflows" icon="plug" href="/cookbooks/integrations/openai-tool-calls">
See a full Node-based workflow that layers Mem0 memories onto tool-calling agents.
<Card title="Add to your framework" icon="plug" href="/integrations">
Wire Mem0 into LangChain, CrewAI, LangGraph, and 20+ more.
</Card>
</CardGroup>