MCP 服务器

MCP fal.ai Image Server

Enables AI-powered image generation from text prompts using fal.ai models directly within IDEs. Supports multiple models, customizable parameters, and saves generated images locally with accessible file paths.

README

MCP fal.ai Image Server

Effortlessly generate images from text prompts using fal.ai and the Model Context Protocol (MCP). Integrates directly with AI IDEs like Cursor and Windsurf.

When and Why to Use

This tool is designed for:

Developers and designers who want to generate images from text prompts without leaving their IDE.
Rapid prototyping of UI concepts, marketing assets, or creative ideas.
Content creators needing unique visuals for blogs, presentations, or social media.
AI researchers and tinkerers experimenting with the latest fal.ai models.
Automating workflows that require programmatic image generation via MCP.

Key features:

Supports any valid fal.ai model and all major image parameters.
Works out of the box with Node.js and a fal.ai API key.
Saves images locally with accessible file paths.
Simple configuration and robust error handling.

Quick Start

Requirements: Node.js 18+, fal.ai API key

Configure MCP:

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

Run: Use the generate-image tool from your IDE.

💡 Typical Workflow: Describe the image you want (e.g., “generate a landscape with flying cars using model fal-ai/kolors, 2 images, landscape_16_9”) and get instant results in your IDE.

🗨️ Example Prompts

generate an image of a red apple
generate an image of a red apple using model fal-ai/kolors
generate 3 images of a glowing red apple in a futuristic city using model fal-ai/recraft-v3, square_hd, 40 inference steps, guidance scale 4.0, safety checker on

Supported parameters: prompt, model ID (any fal.ai model), number of images, image size, inference steps, guidance scale, safety checker.

Images are saved locally; file paths are shown in the response. For model IDs, see fal.ai/models.

Troubleshooting

FAL_KEY environment variable is not set: Set your fal.ai API key as above.
npx not found: Install Node.js 18+ and npm.

<details> <summary>Advanced: Example MCP Request/Response</summary>

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

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

</details>

📁 Image Output Directory

Generated images are saved to your local system:

By default: ~/Downloads/fal_ai (on Linux/macOS; uses XDG standard if available)
Custom location: Set the environment variable FAL_IMAGES_OUTPUT_DIR to your desired folder. Images will be saved in <your-folder>/fal_ai.

The full file path for each image is included in the tool's response.

⚠️ Error Handling & Troubleshooting

If you specify a model ID that is not supported by fal.ai, you will receive an error from the backend. Double-check for typos or visit fal.ai/models to confirm the model ID.
For the latest list of models and their capabilities, refer to the fal.ai model catalog or API docs.
For other errors, consult your MCP client logs or open an issue on GitHub.