🎨 Fal.ai MCP Server

A Model Context Protocol (MCP) server that enables Claude Desktop (and other MCP clients) to generate images, videos, music, and audio using Fal.ai models.

✨ Features

🚀 Performance

• Native Async API - Uses fal_client.run_async() for optimal performance
• Queue Support - Long-running tasks (video/music) use queue API with progress updates
• Non-blocking - All operations are truly asynchronous

🌐 Transport Modes (New!)

• STDIO - Traditional Model Context Protocol communication
• HTTP/SSE - Web-based access via Server-Sent Events
• Dual Mode - Run both transports simultaneously

🎨 Media Generation

• 🖼️ Image Generation - Create images using Flux, SDXL, and other models
• 🎬 Video Generation - Generate videos from images or text prompts
• 🎵 Music Generation - Create music from text descriptions
• 🗣️ Text-to-Speech - Convert text to natural speech
• 📝 Audio Transcription - Transcribe audio using Whisper
• ⬆️ Image Upscaling - Enhance image resolution
• 🔄 Image-to-Image - Transform existing images with prompts

🚀 Quick Start

Prerequisites

• Python 3.10 or higher
• Fal.ai API key (free tier available)
• Claude Desktop (or any MCP-compatible client)

Installation

Option 1: Docker (Recommended for Production) 🐳

Official Docker image available on GitHub Container Registry:

# Pull the latest image
docker pull ghcr.io/raveenb/fal-mcp-server:latest

# Run with your API key
docker run -d \
  --name fal-mcp \
  -e FAL_KEY=your-api-key \
  -p 8080:8080 \
  ghcr.io/raveenb/fal-mcp-server:latest

Or use Docker Compose:

curl -O https://raw.githubusercontent.com/raveenb/fal-mcp-server/main/docker-compose.yml
echo "FAL_KEY=your-api-key" > .env
docker-compose up -d

Option 2: Install from PyPI

pip install fal-mcp-server

Or with uv:

uv pip install fal-mcp-server

Option 3: Install from source

git clone https://github.com/raveenb/fal-mcp-server.git
cd fal-mcp-server
pip install -e .

Configuration

1. Get your Fal.ai API key from fal.ai

2. Configure Claude Desktop by adding to:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

For Docker Installation:

{
  "mcpServers": {
    "fal-ai": {
      "command": "curl",
      "args": ["-N", "http://localhost:8080/sse"]
    }
  }
}

For PyPI Installation:

{
  "mcpServers": {
    "fal-ai": {
      "command": "python",
      "args": ["-m", "fal_mcp_server.server"],
      "env": {
        "FAL_KEY": "your-fal-api-key"
      }
    }
  }
}

For Source Installation:

{
  "mcpServers": {
    "fal-ai": {
      "command": "python",
      "args": ["/path/to/fal-mcp-server/src/fal_mcp_server/server.py"],
      "env": {
        "FAL_KEY": "your-fal-api-key"
      }
    }
  }
}

3. Restart Claude Desktop

💬 Usage

With Claude Desktop

Once configured, ask Claude to:

• "Generate an image of a sunset"
• "Create a video from this image"
• "Generate 30 seconds of ambient music"
• "Convert this text to speech"
• "Transcribe this audio file"

HTTP/SSE Transport (New!)

Run the server with HTTP transport for web-based access:

# Using Docker (recommended)
docker run -d -e FAL_KEY=your-key -p 8080:8080 ghcr.io/raveenb/fal-mcp-server:latest

# Using pip installation
fal-mcp-http --host 0.0.0.0 --port 8000

# Or dual mode (STDIO + HTTP)
fal-mcp-dual --transport dual --port 8000

Connect from web clients via Server-Sent Events:

• SSE endpoint: http://localhost:8080/sse (Docker) or http://localhost:8000/sse (pip)
• Message endpoint: POST http://localhost:8080/messages/

See Docker Documentation and HTTP Transport Documentation for details.

📦 Supported Models

Image Models

• flux_schnell - Fast high-quality generation
• flux_dev - Development version with more control
• sdxl - Stable Diffusion XL

Video Models

• svd - Stable Video Diffusion
• animatediff - Text-to-video animation

Audio Models

• musicgen - Music generation
• bark - Text-to-speech
• whisper - Audio transcription

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Local Development

We support local CI testing with act:

# Quick setup
make ci-local  # Run CI locally before pushing

# See detailed guide
cat docs/LOCAL_TESTING.md

📝 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

• Fal.ai for providing the AI models
• Anthropic for the MCP specification