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

# Quickstart

This guide shows how to connect the RunComfy MCP server to your AI assistant and make your first tool call.

***

## Prerequisites

You need a RunComfy API token. Get yours from your [Profile](https://www.runcomfy.com/profile) page.

> Your API token is sent per-request in the Authorization header and is never stored by the MCP server.

***

## Setup

Choose your AI assistant or MCP client below.

### Claude Code

Run this command in your terminal:

```bash theme={null}
claude mcp add runcomfy \
  --transport streamable-http \
  https://mcp.runcomfy.com/mcp \
  --header "Authorization: Bearer <YOUR_RUNCOMFY_TOKEN>"
```

Replace `<YOUR_RUNCOMFY_TOKEN>` with your API token.

### Cursor

Add the following to your `.cursor/mcp.json` file (create it if it doesn't exist):

```json theme={null}
{
  "mcpServers": {
    "runcomfy": {
      "url": "https://mcp.runcomfy.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_RUNCOMFY_TOKEN>"
      }
    }
  }
}
```

### Windsurf

Go to **Windsurf Settings > MCP** and add the following configuration:

```json theme={null}
{
  "mcpServers": {
    "runcomfy": {
      "serverUrl": "https://mcp.runcomfy.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_RUNCOMFY_TOKEN>"
      }
    }
  }
}
```

### VS Code (Copilot)

Add the following to your `.vscode/mcp.json` file:

```json theme={null}
{
  "servers": {
    "runcomfy": {
      "type": "http",
      "url": "https://mcp.runcomfy.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_RUNCOMFY_TOKEN>"
      }
    }
  }
}
```

### Other MCP clients

Any client that supports **Streamable HTTP** transport can connect:

* **Server URL**: `https://mcp.runcomfy.com/mcp`
* **Transport**: Streamable HTTP
* **Authentication**: `Authorization: Bearer <YOUR_RUNCOMFY_TOKEN>` header on every request

***

## Verify the connection

Once configured, ask your AI assistant:

> "List my RunComfy deployments"

The assistant will call `list_deployments` and return your deployments. If you see a list of deployment names and IDs, the connection is working.

***

## Your first inference

With a deployment available, try:

> "Run my \[deployment name] with the prompt: a futuristic cityscape at sunset"

The assistant will:

1. Call `get_deployment` to inspect the workflow's node IDs
2. Call `submit_request` with the appropriate overrides
3. Call `get_request_status` to poll progress
4. Call `get_request_result` to return the output URL

***

## Next steps

* **[Tool Reference](/mcp/tool-reference)** — Detailed parameters and examples for all 10 tools
* **[FAQ](/mcp/faq)** — Common questions
* **[Serverless API docs](/serverless/introduction)** — Understand deployments, workflows, and the async queue