> ## 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.

# Cognee Cloud & MCP

> How to connect the Cognee MCP server to Cognee Cloud

## Connecting MCP to Cognee Cloud

The Cognee MCP server can connect to your Cognee Cloud tenant using the `--serve-url` and `--serve-api-key` flags. This lets any MCP-compatible client (Claude Desktop, Cursor, VS Code Copilot) work with your cloud-hosted knowledge graph.

|                    | Cognee MCP                                                                    | Cognee Cloud                           |
| ------------------ | ----------------------------------------------------------------------------- | -------------------------------------- |
| **Where it runs**  | Locally on your machine                                                       | Hosted by Cognee                       |
| **Access method**  | MCP protocol                                                                  | `cognee` SDK via `serve()` or Cloud UI |
| **Authentication** | Bearer token (self-hosted)                                                    | `X-Api-Key` header                     |
| **API endpoints**  | Self-hosted backend endpoints such as `/api/v1/remember` and `/api/v1/recall` | Hosted SDK/client flow via `serve()`   |
| **Use case**       | AI IDE tools (Cursor, Claude Code, etc.)                                      | Cloud-managed knowledge graphs         |

### Why `API_URL` only works with self-hosted Cognee backends

The MCP server's `API_URL` / `API_TOKEN` mechanism is designed for **self-hosted Cognee backends**. When the MCP server runs in API mode, it:

* Sends requests to self-hosted Cognee endpoints such as `/api/v1/remember`, `/api/v1/recall`, `/api/v1/improve`, and `/api/v1/forget`
* Authenticates with `Authorization: Bearer <token>`

```bash theme={null}
cognee-mcp --transport sse --port 8001 \
  --serve-url https://your-tenant.aws.cognee.ai \
  --serve-api-key your-api-key
```

Get your API Base URL and API key from the [API Keys](/cognee-cloud/ui/api-keys) page in the Cognee Cloud console.

* Authentication uses the `X-Api-Key` header, not a Bearer token
* The recommended Cloud SDK flow connects through `cognee.serve()` rather than the MCP server's `API_URL` bridge
  For the full setup guide, see [Cloud MCP](/cognee-cloud/connections/cloud-mcp).

<Note>
  The older `API_URL` / `API_TOKEN` environment variables are designed for **self-hosted Cognee backends**, not Cognee Cloud. Use `--serve-url` and `--serve-api-key` for Cloud connections.
</Note>

## Other connection options

<AccordionGroup>
  <Accordion title="Use Cognee MCP for local AI memory (standalone)">
    Run the MCP server in **standalone mode** (no Cloud connection). The server manages its own local knowledge graph.

    ```bash theme={null}
    # Standalone mode — requires LLM_API_KEY
    LLM_API_KEY=sk-... cognee-mcp --transport sse --port 8001
    ```

    This is the simplest way to add persistent memory to Cursor, Claude Code, Cline, and other MCP-compatible tools.
  </Accordion>

  <Accordion title="Use the Python SDK instead">
    Access Cognee Cloud programmatically using the [`cognee` SDK](/cognee-cloud/cognee-cloud-sdk) connected through `serve()`, which handles authentication and communication with the hosted service.

    ```bash theme={null}
    export COGNEE_SERVICE_URL="https://your-tenant.aws.cognee.ai"
    export COGNEE_API_KEY="your-cognee-cloud-api-key"
    ```

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

    async def main():
        await cognee.serve()  # Reads COGNEE_SERVICE_URL and COGNEE_API_KEY
        await cognee.remember("...", dataset_name="my_dataset")
        results = await cognee.recall("...", datasets=["my_dataset"])
        print(results)

    asyncio.run(main())
    ```

    If you prefer not to use environment variables, pass both values directly:

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

    See the [Cloud SDK guide](/cognee-cloud/connections/cloud-sdk) for a complete walkthrough.
  </Accordion>

  <Accordion title="Connect MCP to a self-hosted Cognee backend">
    If you want multiple AI clients to share a single knowledge graph, run a self-hosted Cognee backend and point the MCP server at it using `API_URL` and `API_TOKEN`:

    ```bash theme={null}
    # 1. Start a self-hosted Cognee backend
    docker run -e LLM_API_KEY=your_key -p 8080:8000 --rm -it cognee/cognee:main

    # 2. Start MCP in API mode pointing to your backend
    docker run \
      -e TRANSPORT_MODE=sse \
      -e API_URL=http://localhost:8080 \
      -e API_TOKEN=your_backend_token \
      -p 8000:8000 --rm -it cognee/cognee-mcp:main
    ```

    See the [MCP Quickstart](/cognee-mcp/mcp-quickstart#api-mode-shared-knowledge-graph) for full details on this pattern.
  </Accordion>
</AccordionGroup>