A Model Context Protocol (MCP) server for generating images using Fal.ai's HiDream-I1-Full model
Project description
FAL AI Image Generator MCP
A Model Context Protocol (MCP) server for generating images using the FAL.ai platform and HiDream-ai/HiDream-I1-Full model.
Quick Start
- Get a FAL.ai API Key
- Sign up at FAL.ai and obtain your API key
- Install the package
# Using pip
pip install fal-ai-mcp
# Using uv
uv pip install fal-ai-mcp
- Run and Test the server
# Using Python module
export FAL_KEY="your-fal-api-key" && npx @modelcontextprotocol/inspector -- python -m fal_ai_mcp
# Using uvx (alternative method)
export FAL_KEY="your-fal-api-key" && npx @modelcontextprotocol/inspector uvx fal-ai-mcp
Configure in Claude Desktop, Cursor or Windsurf
Add this configuration to your MCP config file:
Method 1: Using uvx
{
"mcpServers": {
"fal-ai-image-generator": {
"command": "uvx",
"args": [
"fal-ai-mcp"
],
"env": {
"FAL_KEY": "your-fal-api-key"
}
}
}
}
Method 2: Using Python module
{
"mcpServers": {
"fal-ai-image-generator": {
"command": "python",
"args": ["-m", "fal_ai_mcp"],
"env": {
"FAL_KEY": "your-fal-api-key"
}
}
}
}
Features
This MCP server provides a tool for generating high-quality images from text prompts using FAL.ai platform:
- Text-to-image generation using the
text_to_image_faltool - Returns complete metadata including image URL or base64 image data, dimensions, and other information
- Easy integration with MCP-compatible applications
API Reference
text_to_image_fal
Generates an image from a text prompt using the FAL.ai API and HiDream-I1-Full model.
Parameters:
prompt(string): The text description of the image you want to generate
Returns:
- A dictionary containing the generated image data, including:
images: Array of generated images with URLs, dimensions, and content typetimings: Performance metricsseed: The random seed used for generationhas_nsfw_concepts: Safety check resultsprompt: The original prompt
Installation Options
Global Installation
To install the package globally or in your current environment:
# Using pip (recommended)
pip install fal-ai-mcp
# Using uv
uv pip install fal-ai-mcp
If you encounter any issues with the installation, try using the --force-reinstall flag:
pip install fal-ai-mcp --force-reinstall
Installing from Source
# Using pip
pip install git+https://github.com/OKitchen/fal-ai-mcp.git
# Using uv
uv pip install git+https://github.com/OKitchen/fal-ai-mcp.git
Adding as a Project Dependency
To add the package as a dependency to your Python project (requires a pyproject.toml file):
# Navigate to your project directory that has a pyproject.toml
cd your-project-directory
# Add as a dependency using uv
uv add fal-ai-mcp
Note: The uv add command will only work in a Python project that has a pyproject.toml file and is not named fal-ai-mcp (to avoid circular dependencies).
Locally Runing the Server
uv run mcp dev src/fal_ai_mcp/fal_ai_mcp.py
Troubleshooting
Python Version Requirements
This package requires Python 3.10 or higher. If you encounter an error like:
ERROR: Could not find a version that satisfies the requirement fal-ai-mcp
ERROR: No matching distribution found for fal-ai-mcp
Make sure you're using Python 3.10 or higher:
python --version
Module Not Found
If you encounter an error like:
No module named fal_ai_mcp
Make sure the package is properly installed:
pip list | grep fal-ai-mcp
If it's not listed, try reinstalling:
pip install --force-reinstall fal-ai-mcp
FAL API Key Not Set
If you see an error about missing FAL API keys:
ValueError: Neither FAL_API_KEY nor FAL_KEY environment variables are set
Make sure to set your FAL.ai API key before running the server:
export FAL_KEY="your-fal-api-key"
Development
To set up the development environment:
# Clone the repository
git clone https://github.com/OKitchen/fal-ai-mcp.git
cd fal-ai-mcp
# Set up a virtual environment
uv init
uv pip install -e .
# Run the server locally with your FAL.ai API key
export FAL_KEY="your-fal-api-key" && uv run -m fal_ai_mcp
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