fal-ai/ideogram/v3 MCP Server

A Model Context Protocol (MCP) server that provides access to the fal-ai/ideogram/v3 image generation model. This server allows you to generate high-quality images with superior text rendering capabilities using advanced AI technology through the fal.ai platform.

Features

• High-Quality Image Generation: Generate stunning images using the fal-ai/ideogram/v3 model
• Superior Text Rendering: Advanced text-to-image generation with excellent text quality
• Multiple Generation Methods: Support for synchronous and queue-based generation
• Flexible Image Sizing: Support for predefined sizes and custom dimensions
• Advanced Style Control: Style presets, style codes, and color palettes
• Style Reference Images: Use reference images to guide the generation style
• Local Image Download: Automatically downloads generated images to local storage
• Queue Management: Submit long-running requests and check their status
• Webhook Support: Optional webhook notifications for completed requests

Installation

1. Clone this repository:

git clone https://github.com/PierrunoYT/fal-ideogram-v3-mcp-server.git
cd fal-ideogram-v3-mcp-server

2. Install dependencies:

npm install

3. Build the project:

npm run build

Configuration

Environment Variables

Set your fal.ai API key as an environment variable:

export FAL_KEY="your_fal_api_key_here"

You can get your API key from fal.ai.

MCP Client Configuration

Add this server to your MCP client configuration. For example, in Claude Desktop's config file:

{
  "mcpServers": {
    "fal-ideogram-v3": {
      "command": "npx",
      "args": ["-y", "https://github.com/PierrunoYT/fal-ideogram-v3-mcp-server.git"],
      "env": {
        "FAL_KEY": "your_fal_api_key_here"
      }
    }
  }
}

If the package is published to npm, you can use:

{
  "mcpServers": {
    "fal-ideogram-v3": {
      "command": "npx",
      "args": ["fal-ideogram-v3-mcp-server"],
      "env": {
        "FAL_KEY": "your_fal_api_key_here"
      }
    }
  }
}

Alternatively, if you've cloned the repository locally:

{
  "mcpServers": {
    "fal-ideogram-v3": {
      "command": "node",
      "args": ["/path/to/fal-ideogram-v3-mcp-server/build/index.js"],
      "env": {
        "FAL_KEY": "your_fal_api_key_here"
      }
    }
  }
}

Available Tools

1. ideogram_v3_generate

Generate images using the standard synchronous method.

Parameters:

• prompt (required): Text description of the image to generate
• negative_prompt (optional): What you don't want in the image
• image_size (optional): Predefined size or custom {width, height} object (default: "square_hd")
• rendering_speed (optional): "TURBO", "BALANCED", or "QUALITY" (default: "BALANCED")
• style (optional): "AUTO", "GENERAL", "REALISTIC", or "DESIGN"
• style_codes (optional): Array of 8-character hexadecimal style codes
• color_palette (optional): Color palette preset or custom RGB colors
• image_urls (optional): Array of style reference image URLs
• expand_prompt (optional): Use MagicPrompt enhancement (default: true)
• num_images (optional): Number of images to generate (1-4, default: 1)
• seed (optional): Random seed for reproducible results
• sync_mode (optional): Wait for completion (default: true)

Example:

{
  "prompt": "The Bone Forest stretched across the horizon, its trees fashioned from the ossified remains of ancient leviathans that once swam through the sky. In sky writes \"Ideogram V3 in fal.ai\"",
  "image_size": "square_hd",
  "rendering_speed": "BALANCED",
  "style": "GENERAL"
}

2. ideogram_v3_generate_queue

Submit a long-running image generation request to the queue.

Parameters: Same as ideogram_v3_generate plus:

• webhook_url (optional): URL for webhook notifications

Returns: A request ID for tracking the job

3. ideogram_v3_queue_status

Check the status of a queued request.

Parameters:

• request_id (required): The request ID from queue submission
• logs (optional): Include logs in response (default: true)

4. ideogram_v3_queue_result

Get the result of a completed queued request.

Parameters:

• request_id (required): The request ID from queue submission

Image Sizes

Predefined Sizes

• square_hd: High-definition square
• square: Standard square
• portrait_4_3: Portrait 4:3 aspect ratio
• portrait_16_9: Portrait 16:9 aspect ratio
• landscape_4_3: Landscape 4:3 aspect ratio
• landscape_16_9: Landscape 16:9 aspect ratio

Custom Sizes

You can also specify custom dimensions:

{
  "image_size": {
    "width": 1280,
    "height": 720
  }
}

Style Control

Style Presets

Use predefined styles:

{
  "style": "REALISTIC"
}

Style Codes

Use 8-character hexadecimal style codes:

{
  "style_codes": ["A1B2C3D4", "E5F6A7B8"]
}

Note: Cannot use both style and style_codes together.

Color Palettes

Preset Palettes

{
  "color_palette": {
    "name": "EMBER"
  }
}

Available presets: EMBER, FRESH, JUNGLE, MAGIC, MELON, MOSAIC, PASTEL, ULTRAMARINE

Custom Color Palettes

{
  "color_palette": {
    "members": [
      {
        "rgb": {"r": 255, "g": 0, "b": 0},
        "color_weight": 0.7
      },
      {
        "rgb": {"r": 0, "g": 255, "b": 0},
        "color_weight": 0.3
      }
    ]
  }
}

Style Reference Images

Use reference images to guide the generation style:

{
  "image_urls": [
    "https://example.com/style-reference1.jpg",
    "https://example.com/style-reference2.png"
  ]
}

Note: Maximum total size of 10MB across all style references. Supported formats: JPEG, PNG, WebP.

Rendering Speed

Control the quality vs speed trade-off:

• TURBO: Fastest generation, lower quality
• BALANCED: Good balance of speed and quality (default)
• QUALITY: Highest quality, slower generation

Output

Generated images are automatically downloaded to a local images/ directory with descriptive filenames. The response includes:

• Local file paths
• Original URLs
• Image dimensions (when available)
• Content types
• File sizes (when available)
• Generation parameters used
• Request IDs for tracking
• Seed values for reproducibility

Error Handling

The server provides detailed error messages for:

• Missing API keys
• Invalid parameters
• Conflicting parameters (e.g., using both style and style_codes)
• Network issues
• API rate limits
• Generation failures

Development

Running in Development Mode

npm run dev

Testing the Server

npm test

Getting the Installation Path

npm run get-path

API Reference

This server implements the fal-ai/ideogram/v3 API. For detailed API documentation, visit:

• fal.ai Documentation
• fal.ai Client Library

Examples

Basic Text-to-Image Generation

{
  "prompt": "A majestic dragon soaring through clouds with 'Hello World' written in the sky"
}

Advanced Generation with Style Control

{
  "prompt": "A cyberpunk cityscape at night",
  "style": "DESIGN",
  "color_palette": {"name": "ULTRAMARINE"},
  "rendering_speed": "QUALITY",
  "image_size": "landscape_16_9"
}

Using Style Reference Images

{
  "prompt": "A portrait of a woman in Renaissance style",
  "image_urls": ["https://example.com/renaissance-painting.jpg"],
  "style": "REALISTIC"
}

Queue-based Generation with Webhook

{
  "prompt": "A detailed architectural drawing of a futuristic building",
  "rendering_speed": "QUALITY",
  "webhook_url": "https://your-server.com/webhook"
}

License

MIT License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Support

For issues and questions:

• Open an issue on GitHub
• Check the fal.ai documentation

Changelog

v1.0.0

• Initial release with fal-ai/ideogram/v3 API support
• Text-to-image generation with superior text rendering
• Style control with presets, codes, and color palettes
• Style reference image support
• Queue management with webhook support
• Local image download functionality
• Comprehensive error handling