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

# Cloud SDK

> Connect to Cognee Cloud programmatically using the Cognee Python SDK

The Cognee Python SDK connects to Cognee Cloud via `cognee.serve()`. Once connected, all operations (`remember`, `recall`, `forget`, `improve`) route to your cloud tenant.

<Note>
  The same `cognee` package is used for both local and cloud workflows. The only difference is calling `cognee.serve()` to connect to a remote instance.
</Note>

## Install

```bash theme={null}
pip install cognee
```

## Complete example

```python theme={null}
import asyncio
import cognee

async def main():
    # Connect to Cognee Cloud
    await cognee.serve(
        url="https://your-tenant.aws.cognee.ai",
        api_key="your-api-key"
    )

    # Store content in memory — ingests, builds knowledge graph, enriches
    await cognee.remember(
        "Cognee Cloud automates knowledge graph creation in the cloud.",
        dataset_name="default_dataset",
    )

    # Retrieve from memory
    results = await cognee.recall(
        query_text="What does Cognee Cloud automate?",
    )
    for result in results:
        print(result)

    # Disconnect when done
    await cognee.disconnect()

asyncio.run(main())
```

## What just happened

### Connecting to cloud

Pass your tenant URL and API key to `cognee.serve()`:

```python theme={null}
await cognee.serve(
    url="https://your-tenant.aws.cognee.ai",
    api_key="your-api-key"
)
```

Create an API key from the [API Keys](/cognee-cloud/ui/api-keys) page in the Cognee Cloud console. You can find your tenant URL there as well.

### Storing data

```python theme={null}
await cognee.remember(
    "Cognee Cloud automates knowledge graph creation in the cloud.",
    dataset_name="default_dataset",
)
```

[`remember`](/core-concepts/main-operations/remember) ingests data and builds the knowledge graph in a single call. Data is organized by [dataset](/core-concepts/further-concepts/datasets) for isolation and permissions.

For more control, use the lower-level [`add`](/core-concepts/main-operations/legacy-operations/add) and [`cognify`](/core-concepts/main-operations/legacy-operations/cognify) operations separately.

### Retrieving data

```python theme={null}
results = await cognee.recall(
    query_text="What does Cognee Cloud automate?",
)
```

[`recall`](/core-concepts/main-operations/recall) auto-routes the query to the best retrieval strategy. For direct control over search types, see [Search Basics](/guides/search-basics).

### Disconnecting

```python theme={null}
await cognee.disconnect()
```

Closes the connection to the cloud tenant. Credentials remain cached for the next session.

## Next steps

<CardGroup cols={2}>
  <Card title="Cloud functionality" href="/cognee-cloud/functionality/data-ingestion" icon="cloud">
    Explore the full API surface available in Cognee Cloud.
  </Card>

  <Card title="Cloud MCP" href="/cognee-cloud/connections/cloud-mcp" icon="plug">
    Connect MCP-compatible clients to Cognee Cloud.
  </Card>
</CardGroup>