> ## 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 MCP

> Connect MCP-compatible clients to Cognee Cloud

Cognee runs as an [MCP (Model Context Protocol)](https://modelcontextprotocol.io) server. Any MCP-compatible client (Claude Desktop, Cursor, VS Code Copilot) can connect to it as a tool provider. The MCP server can run locally or connect to your Cognee Cloud tenant.

## Step 1 — Start the MCP server

Connect the MCP server to Cognee Cloud using your API Base URL and API key from the [API Keys](/cognee-cloud/ui/api-keys) page:

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

<Note>
  For **local mode** (no Cloud connection), omit the `--serve-url` and `--serve-api-key` flags. The server will manage its own local knowledge graph. Local mode requires an `LLM_API_KEY` environment variable.
</Note>

## Step 2 — Add to your MCP client config

Add Cognee as a tool server in your MCP client's configuration. For an SSE connection to a running server, point the client at the server URL:

```json theme={null}
{
  "mcpServers": {
    "cognee": {
      "url": "http://localhost:8001/sse"
    }
  }
}
```

Alternatively, you can run the server over **stdio** — the client launches `cognee-mcp` itself. Install it with `pip install cognee-mcp`, then use this config (this is the form the in-product **Integrations** page generates):

```json theme={null}
{
  "mcpServers": {
    "cognee": {
      "command": "cognee-mcp",
      "env": {
        "COGNEE_BASE_URL": "https://your-tenant.aws.cognee.ai",
        "COGNEE_API_KEY": "your-api-key"
      }
    }
  }
}
```

For per-client config file locations (Claude Desktop, Cursor, Hermes, VS Code, Gemini CLI, Cline), see [Integrations](/cognee-cloud/ui/integrations).

## Step 3 — Available tools

Once connected, your MCP client gets the Cognee API v1 memory tools:

| Tool       | Description                                      |
| ---------- | ------------------------------------------------ |
| `remember` | Store data in memory (add + cognify in one step) |
| `recall`   | Search memory with auto-routing                  |
| `forget`   | Delete data from memory                          |

For detailed setup per client, see the [MCP integration guides](/cognee-mcp/integrations/claude-code).

## Next steps

<CardGroup cols={2}>
  <Card title="Cloud SDK" href="/cognee-cloud/connections/cloud-sdk" icon="terminal">
    Connect to Cognee Cloud programmatically using the Python SDK.
  </Card>

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