About fal-api-mcp-server
fal-api-mcp-server is an MCP server for image-generation workflows, using fal.ai's FLUX.1 Pro to create images from text prompts with configurable size, quantity, and format.
Key features
- 01Generate images with FLUX.1 Pro
- 02Set image size and quantity
- 03Choose JPEG or PNG output
- 04Configure safety checks and tolerance
Use cases
- 01Generate landscapes from text prompts
- 02Create character portraits or city concepts
MCP support
The MCP server exposes a generate_image tool to MCP clients for image generation with fal.ai FLUX.1 Pro. It requires a fal.ai API key provided through FAL_KEY.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEfal-api-mcp-server
A Model Context Protocol (MCP) server that provides image generation capabilities using fal.ai's FLUX.1 Pro model.
Components
Resources
This server does not provide any persistent resources as fal.ai is primarily a stateless model execution service.
Tools
The server implements one tool:
- generate_image: Generates images based on text prompts using fal.ai FLUX.1 Pro
- Required parameters:
prompt: The text prompt to generate the image from
- Optional parameters:
image_size: The desired image size (default: "landscape_4_3")- Options: "square_hd", "square", "portrait_4_3", "portrait_16_9", "landscape_4_3", "landscape_16_9"
num_images: The number of images to generate (default: 1)enable_safety_checker: Enable the safety checker (default: true)safety_tolerance: Safety tolerance level 1-6, higher is more permissive (default: "2")output_format: Output image format, "jpeg" or "png" (default: "jpeg")
- Required parameters:
Configuration
This server requires a fal.ai API key to function properly. You can obtain an API key by signing up at fal.ai.
The API key should be provided as an environment variable:
FAL_KEY=your_fal_ai_api_key
You can set this environment variable in your shell, or create a .env file in the same directory as the server with the above content.
Demo
https://github.com/user-attachments/assets/564a0fc3-9204-4399-b1ea-ab6a5c9f2d84
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
"mcpServers": {
"fal-api-mcp-server": {
"command": "uv",
"args": [
"--directory",
"/path/to/fal-api-mcp-server",
"run",
"fal-api-mcp-server"
],
"env": {
"FAL_KEY": "your_fal_ai_api_key"
}
}
}
Published Servers Configuration
"mcpServers": {
"fal-api-mcp-server": {
"command": "uvx",
"args": [
"fal-api-mcp-server"
],
"env": {
"FAL_KEY": "your_fal_ai_api_key"
}
}
}
Usage
Once the server is configured and running, you can use it with Claude to generate images. Example prompts:
- "Generate an image of a mountain landscape at sunset"
- "Create a portrait of a cyberpunk character with neon lights"
- "Show me a futuristic cityscape with flying cars"
Claude will use the fal.ai FLUX.1 Pro model to generate the requested images.
Development
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory /path/to/fal-api-mcp-server run fal-api-mcp-server
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.