fal-minimax-image-01 MCP Server
Enables high-quality AI image generation using MiniMax (Hailuo AI) text-to-image technology through fal.ai, supporting multiple aspect ratios, prompt optimization, and both synchronous and queue-based generation with automatic local image downloads.
README
fal-ai/minimax/image-01 MCP Server
A Model Context Protocol (MCP) server that provides access to the fal-ai/minimax/image-01 image generation model. This server allows you to generate high-quality images using MiniMax (Hailuo AI) Text to Image technology through the fal.ai platform.
Features
- High-Quality Image Generation: Generate stunning images using the fal-ai/minimax/image-01 model
- MiniMax (Hailuo AI) Technology: Advanced text-to-image generation with excellent quality
- Multiple Generation Methods: Support for synchronous and queue-based generation
- Flexible Aspect Ratios: Support for various aspect ratios from square to panoramic
- Prompt Optimization: Optional prompt enhancement for better results
- 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
- Stylized and Realistic Output: Supports both stylized and photorealistic image generation
Installation
- Clone this repository:
git clone https://github.com/PierrunoYT/fal-minimax-image-01-mcp-server.git
cd fal-minimax-image-01-mcp-server
- Install dependencies:
npm install
- 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-minimax-image-01": {
"command": "npx",
"args": ["-y", "https://github.com/PierrunoYT/fal-minimax-image-01-mcp-server.git"],
"env": {
"FAL_KEY": "your_fal_api_key_here"
}
}
}
}
If the package is published to npm, you can use:
{
"mcpServers": {
"fal-minimax-image-01": {
"command": "npx",
"args": ["fal-minimax-image-01-mcp-server"],
"env": {
"FAL_KEY": "your_fal_api_key_here"
}
}
}
}
Alternatively, if you've cloned the repository locally:
{
"mcpServers": {
"fal-minimax-image-01": {
"command": "node",
"args": ["/path/to/fal-minimax-image-01-mcp-server/build/index.js"],
"env": {
"FAL_KEY": "your_fal_api_key_here"
}
}
}
}
Available Tools
1. minimax_generate
Generate images using the standard synchronous method.
Parameters:
prompt(required): Text prompt for image generation (max 1500 characters). Longer text prompts will result in better quality images.aspect_ratio(optional): Aspect ratio of the generated image (default: "1:1")num_images(optional): Number of images to generate (1-9, default: 1)prompt_optimizer(optional): Whether to enable automatic prompt optimization (default: false)
Example:
{
"prompt": "Man dressed in white t shirt, full-body stand front view image, outdoor, Venice beach sign, full-body image, Los Angeles, Fashion photography of 90s, documentary, Film grain, photorealistic",
"aspect_ratio": "16:9",
"num_images": 2,
"prompt_optimizer": true
}
2. minimax_generate_queue
Submit a long-running image generation request to the queue.
Parameters: Same as minimax_generate plus:
webhook_url(optional): URL for webhook notifications
Returns: A request ID for tracking the job
3. minimax_queue_status
Check the status of a queued request.
Parameters:
request_id(required): The request ID from queue submissionlogs(optional): Include logs in response (default: true)
4. minimax_queue_result
Get the result of a completed queued request.
Parameters:
request_id(required): The request ID from queue submission
API Information
- Endpoint:
https://fal.run/fal-ai/minimax/image-01 - Model ID:
fal-ai/minimax/image-01 - Category: text-to-image
- Kind: inference
- Tags: stylized, realism
Aspect Ratios
The MiniMax model supports the following aspect ratios:
1:1: Square format (default)16:9: Widescreen landscape4:3: Standard landscape3:2: Classic photo landscape2:3: Classic photo portrait3:4: Standard portrait9:16: Vertical/mobile format21:9: Ultra-wide panoramic
Example:
{
"aspect_ratio": "16:9"
}
Prompt Optimization
Enable prompt optimization to enhance your text prompts for better results:
{
"prompt_optimizer": true
}
When enabled, the AI will automatically improve your prompt to generate higher quality images. This is disabled by default.
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
- Generation parameters used
- Request IDs for tracking
Error Handling
The server provides detailed error messages for:
- Missing API keys
- Invalid parameters
- Network issues
- API rate limits
- Generation failures
- Prompt length violations (max 1500 characters)
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/minimax/image-01 API. For detailed API documentation, visit:
Examples
Basic Text-to-Image Generation
{
"prompt": "A majestic dragon soaring through clouds, fantasy art style, detailed scales, dramatic lighting"
}
Photorealistic Portrait
{
"prompt": "Man dressed in white t shirt, full-body stand front view image, outdoor, Venice beach sign, full-body image, Los Angeles, Fashion photography of 90s, documentary, Film grain, photorealistic",
"aspect_ratio": "2:3",
"prompt_optimizer": true
}
Landscape Image with Optimization
{
"prompt": "A serene mountain landscape at sunset, golden hour lighting, misty valleys, snow-capped peaks, cinematic composition, high resolution nature photography",
"aspect_ratio": "16:9",
"prompt_optimizer": true
}
Multiple Images Generation
{
"prompt": "A cute cartoon cat in different poses, kawaii style, pastel colors, chibi art, adorable expressions",
"aspect_ratio": "1:1",
"num_images": 4
}
Ultra-wide Panoramic Scene
{
"prompt": "A detailed architectural visualization of a futuristic smart city with sustainable technology, flying vehicles, green buildings, advanced infrastructure, panoramic view",
"aspect_ratio": "21:9",
"prompt_optimizer": true
}
Queue-based Generation with Webhook
{
"prompt": "Epic fantasy battle scene with dragons and knights, medieval castle in background, dramatic sky, detailed armor and weapons, cinematic lighting, high fantasy art",
"aspect_ratio": "16:9",
"num_images": 3,
"webhook_url": "https://your-server.com/webhook"
}
Tips for Better Results
- Use Detailed Prompts: Longer, more descriptive prompts generally produce better quality images
- Enable Prompt Optimization: Use
prompt_optimizer: truefor enhanced results - Choose Appropriate Aspect Ratios: Match the aspect ratio to your intended use case
- Be Specific: Include details about style, lighting, composition, and quality level
- Use Style Keywords: Terms like "photorealistic", "cinematic", "detailed", "high resolution" can improve output
License
MIT License - see LICENSE file for details.
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- 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/minimax/image-01 API support
- MiniMax (Hailuo AI) Text to Image generation with superior capabilities
- Support for multiple aspect ratios (1:1 to 21:9)
- Prompt optimization for enhanced results (disabled by default)
- Queue management with webhook support
- Local image download functionality
- Support for generating up to 9 images per request
- Comprehensive error handling
- Updated API schema matching latest fal.ai specifications
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。