### Example MCP Request for Image Generation (JSON)

Source: https://github.com/madhusudan-kulkarni/mcp-fal-ai-image/blob/main/README.md

This JSON object demonstrates a typical request sent from an MCP client (like an IDE) to the fal.ai image server. It specifies the 'generate-image' tool and provides arguments such as the text prompt and the desired fal.ai model ID.

```JSON
{
  "tool": "generate-image",
  "args": {
    "prompt": "A futuristic cityscape at sunset",
    "model": "fal-ai/kolors"
  }
}
```

--------------------------------

### Example MCP Response with Image URLs (JSON)

Source: https://github.com/madhusudan-kulkarni/mcp-fal-ai-image/blob/main/README.md

This JSON object illustrates the expected response from the fal.ai image server after successfully generating images. It contains an array of image objects, each providing a local file URL where the generated image can be accessed.

```JSON
{
  "images": [
    { "url": "file:///path/to/generated_image1.png" },
    { "url": "file:///path/to/generated_image2.png" }
  ]
}
```

--------------------------------

### Configuring MCP Server for fal.ai Image Generation (JSON)

Source: https://github.com/madhusudan-kulkarni/mcp-fal-ai-image/blob/main/README.md

This JSON snippet shows how to configure an IDE's Model Context Protocol (MCP) settings to integrate the mcp-fal-ai-image server. It specifies the command to run the server using npx and sets the FAL_KEY environment variable with your fal.ai API key.

```JSON
{
  "mcpServers": {
    "fal-ai-image": {
      "command": "npx",
      "args": ["-y", "mcp-fal-ai-image"],
      "env": { "FAL_KEY": "YOUR-FAL-AI-API-KEY" }
    }
  }
}
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.