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

# Use MCP servers in prompts

> Connect to Model Context Protocol servers to access external tools and data sources from your prompts

The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) is an open protocol that enables AI models to securely access external data sources, tools, and resources through a standardized interface. Adaline's Editor lets you connect to remote MCP servers and use their tools directly in your prompts — enabling powerful integrations without custom backend code.

## Enable MCP

**1. Select a compatible model**

Open the model selector and choose an LLM that supports MCP integration.

> [!WARNING]
>
> MCP integration currently requires selecting an **Anthropic** model. If you need MCP support for other providers, contact [support@adaline.ai](mailto:support@adaline.ai) for a private preview.

**2. Open MCP settings**

In the model settings panel, select **MCP**.

![Selecting MCP in Adaline](https://mintcdn.com/adaline/-Bsa4BuK4fSdmy67/images/iterate/select-mcp.png?fit=max\&auto=format\&n=-Bsa4BuK4fSdmy67\&q=85\&s=0cb61d71edece43fc2a55095725b1bf1)

**3. Toggle MCP on**

Set the MCP toggle to **On** to enable the integration.

![Enabling MCP in Adaline](https://mintcdn.com/adaline/-Bsa4BuK4fSdmy67/images/iterate/mcp-toggle-on.png?fit=max\&auto=format\&n=-Bsa4BuK4fSdmy67\&q=85\&s=7922948221f307c77925e10a98be4980)

Once enabled, the Editor displays the MCP configuration panel where you can add your server settings:

![MCP integration ready in Adaline](https://mintcdn.com/adaline/-Bsa4BuK4fSdmy67/images/iterate/mcp-integration-ready.png?fit=max\&auto=format\&n=-Bsa4BuK4fSdmy67\&q=85\&s=b6e398fc56118095fb969dd7f0b52b22)

## Configure an MCP server

Each MCP server requires a JSON configuration object. Here is the complete schema:

```json theme={null}
{
  "type": "url",
  "url": "https://example-server.modelcontextprotocol.io/sse",
  "name": "example-mcp",
  "tool_configuration": {
    "enabled": true,
    "allowed_tools": ["example_tool_1", "example_tool_2"]
  },
  "authorization_token": "YOUR_TOKEN"
}
```

### Configuration reference

| Field | Type | Required | Description |
| - | - | - | - |
| `type` | String | Yes | Currently only `"url"` is supported. |
| `url` | String | Yes | The MCP server URL. Must start with `https://`. |
| `name` | String | Yes | A unique identifier for the server. Choose a descriptive name. |
| `tool_configuration` | Object | No | Controls which tools from the server are available. |
| `tool_configuration.enabled` | Boolean | No | Whether to enable tools from the server (default: `true`). |
| `tool_configuration.allowed_tools` | Array | No | Restrict which tools are allowed. By default, all tools are available. |
| `authorization_token` | String | No | OAuth authorization token, if required by the server. |

## Connect to multiple servers

You can connect to multiple MCP servers simultaneously by providing an array of server configurations:

```json theme={null}
[
  {
    "type": "url",
    "url": "https://mcp.example1.com/sse",
    "name": "mcp-server-1",
    "authorization_token": "YOUR_TOKEN_1"
  },
  {
    "type": "url",
    "url": "https://mcp.example2.com/sse",
    "name": "mcp-server-2",
    "authorization_token": "YOUR_TOKEN_2"
  }
]
```

Each server's tools become available to the model independently. The model can choose which server's tools to invoke based on the conversation context.

## Authentication

Many MCP servers require OAuth authentication. To obtain an access token:

1. Use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) or your server provider's OAuth flow to generate a token.
2. Paste the token into the `authorization_token` field in your server configuration.

> [!NOTE]
>
> Keep your authorization tokens secure. If your MCP server's tokens have an expiry, you will need to refresh them periodically.

## Next steps

> [card] [Use Tools in Prompts](https://www.adaline.ai/docs/iterate/use-tools-in-prompt.md)
>
> Define custom tools with JSON schemas and HTTP backends.

> [card] [Tool Calls in Playground](https://www.adaline.ai/docs/iterate/tool-calls-in-playground.md)
>
> Test MCP-powered and tool-powered prompts in the Playground.


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