Grok2 Image Generator MCP server

The Grok2 Image MCP Server allows chat assistants to generate images using the Grok-2 model through the Model Context Protocol (MCP). This server acts as a bridge between chat applications and xAI's image generation capabilities.

Installation

Using npx (Recommended)

You can quickly start the server using npx:

npx -y grok2-image-mcp-server

To configure your MCP configuration file, add the following JSON:

{
    "mcpServers": {
        "grok2_image": {
            "command": "npx",
            "args": [
                "grok2-image-mcp-server"
            ],
            "env": {
                "XAIAPI_KEY": "xAI Key"
            }
        }
    }
}

Configuration Options

Environment Variables

The server supports several environment variables for configuration:

• XAIAPI_KEY (required): Your xAI API key
• XAIAPI_BASE_URL (optional): API proxy URL if you can't access the default endpoint (https://api.x.ai/v1). Must end with /v1
• IMAGE_PROXY_DOMAIN (optional): Image proxy domain to use instead of the default imgen.x.ai
• HTTP_PROXY (optional): Network proxy server address for HTTP/HTTPS connections

Configuration Examples

Using an API proxy:

XAIAPI_BASE_URL=https://api-proxy.me/xai/v1

Using an image proxy domain:

IMAGE_PROXY_DOMAIN=https://image.proxy.workers.dev

Using an HTTP proxy:

HTTP_PROXY=http://127.0.0.1:7890
# or with authentication
HTTP_PROXY=https://user:[email protected]:8080

Setting Up Image Proxy with Cloudflare Workers

If you're experiencing issues accessing images, you can set up a Cloudflare Workers proxy:

1. Copy the following code to a new Cloudflare Worker:

addEventListener('fetch', event => {
  event.respondWith(handleRequest(event.request))
})

const TARGET_DOMAIN = 'imgen.x.ai'

async function handleRequest(request) {
  const url = new URL(request.url)
  const targetUrl = `https://${TARGET_DOMAIN}${url.pathname}${url.search}`

  const init = {
    method: request.method,
    headers: request.headers,
    body: request.method === 'GET' || request.method === 'HEAD' ? undefined : request.body,
    redirect: 'follow'
  }

  const response = await fetch(targetUrl, init)

  const newHeaders = new Headers(response.headers)
  newHeaders.set('Access-Control-Allow-Origin', '*')

  return new Response(response.body, {
    status: response.status,
    statusText: response.statusText,
    headers: newHeaders
  })
}

2. Deploy the Worker and bind a custom domain
3. Configure the IMAGE_PROXY_DOMAIN environment variable with your custom domain (e.g., https://image.proxy.workers.dev)

How to add this MCP server to Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.