What is Fal Ai Mcp Server

fal-ai-mcp-server is an MCP (Model Context Protocol) server designed to utilize the fal.ai APIs for generating images and videos. It serves as a foundational server that can be extended to integrate various fal.ai models and API endpoints.

Use cases

Use cases for fal-ai-mcp-server include generating promotional videos, creating custom images for marketing, and developing interactive media applications that require dynamic content generation.

How to use

To use fal-ai-mcp-server, install uv and configure it in an MCP config using uvx. You can also clone the repository and run the server using uv with a specified directory. Ensure to set the environment variables FAL_KEY and SAVE_MEDIA_DIR appropriately.

Key features

Key features of fal-ai-mcp-server include its extensibility to support different fal.ai models, the ability to generate both images and videos, and a straightforward setup process using uv and MCP configurations.

Where to use

fal-ai-mcp-server can be used in various fields such as digital content creation, media production, and any application requiring image and video generation through AI.

Fal AI MCP Server

An MCP (Model Context Protocol) server to use the fal.ai APIs to generate images and videos.
This is a barebones server that anyone can extend to use different fal.ai models and API endpoints.

Usage

Install uv and add the server to an MCP config using uvx:

{
  "name": "fal-ai-mcp-server",
  "command": "uvx",
  "args": [
    "fal-ai-mcp-server"
  ],
  "env": {
    "FAL_KEY": "your-key",
    "SAVE_MEDIA_DIR": "path/to/save/images"
  }
}

or clone the repo and use uv with a directory:

{
  "name": "fal-ai-mcp-server",
  "command": "uv",
  "args": [
    "--directory",
    "path/to/root/dir/",
    "run",
    "main.py"
  ],
  "env": {
    "FAL_KEY": "your-key",
    "SAVE_MEDIA_DIR": "path/to/save/images"
  }
}

Development

Testing

Clone the repo and use mcp-client-for-testing to test the tools of the server.

uvx mcp-client-for-testing \
    --config '
    [
        {
            "name": "fal-ai-mcp-server",
            "command": "uv",
            "args": [
                "--directory", 
                "path/to/root/dir/", 
                "run", 
                "main.py"
            ],
            "env": {
                "FAL_KEY": "your-key",
                "SAVE_MEDIA_DIR": "path/to/save/images"
            }
        }
    ]
    ' \
    --tool_call '{"name": "echo_tool", "arguments": {"message": "Hello, world!"}}'

Formatting and Linting

The code is formatted and linted with ruff:

uv run ruff format
uv run ruff check --fix

Building with uv

Build the package using uv:

uv build

Releasing a New Version

To release a new version of the package to PyPI, create and push a new Git tag:

1. Checkout the main branch and get the current version:

   git checkout main
   git pull origin main
   git describe --tags
   

2. Create and push a new Git tag:

   git tag v0.2.0
   git push origin v0.2.0
   

The GitHub Actions workflow will automatically build and publish the package to PyPI when a new tag is pushed.
The python package version number will be derived directly from the Git tag.

License

This project is licensed under the MIT License. See the LICENSE file for details.