MCPs
Fal.ai MCP Server

Fal.ai MCP Server

MCP server for multimodal media generation using Fal.ai models.

Stars

Forks

Watchers

Issues

Fal.ai MCP Server is a Model Context Protocol (MCP) compliant server that enables clients like Claude Desktop and others to generate images, videos, music, audio, and transcriptions using Fal.ai models. It offers native asynchronous operation and supports both STDIO and HTTP/SSE transports for flexible integration. The server provides high-performance media generation, including upscaling, text-to-speech, audio transcription, and image-to-image transformations, all powered by Fal.ai's API. Easy deployment options are available via Docker, PyPI, or from source.

Key Features

MCP 1.0 protocol compliance

Native asynchronous API for optimal performance

Support for image, video, music, and audio generation

Audio transcription using Whisper

Image upscaling and image-to-image transformation

Dual transport modes: STDIO and HTTP/SSE

Progressive updates for long-running tasks via queue API

Seamless integration with Claude Desktop and other MCP clients

Easy deployment via Docker, PyPI, or source

Environment variable based API key management

Use Cases

Integrating Fal.ai media generation models into MCP-compatible clients

Generating AI-powered images, videos, or sounds from text prompts

Creating music or soundscapes from textual descriptions

Transcribing audio content using Whisper

Enhancing the resolution of images through upscaling

Transforming or editing images with prompt-based inputs

Providing custom AI media generation in desktop applications

Running scalable, asynchronous media generation services

Automating multimedia content creation pipelines

Enabling text-to-speech conversion and natural speech synthesis

README

🎨 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:

bash

# 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:

bash

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

bash

pip install fal-mcp-server

Or with uv:

bash

uv pip install fal-mcp-server

Option 3: Install from source

bash

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

Configuration

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

json

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

For PyPI Installation:

json

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

For Source Installation:

json

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

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:

bash

# 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:

bash

# 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

Star History

Repository Owner

raveenb

User

Repository Details

Language Python

Default Branch main

Size 172 KB

Contributors 1

License MIT License

MCP Verified Nov 11, 2025

Programming Languages

Python

92.06%

Shell

2.88%

Makefile

2.73%

Dockerfile

2.33%

Topics

ai-tools claude fal-ai image-generation llm mcp model-context-protocol

Join Our Newsletter

Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.

Related MCPs

Discover similar Model Context Protocol servers

Outsource MCP

Unified MCP server for multi-provider AI text and image generation

Outsource MCP is a Model Context Protocol server that bridges AI applications with multiple model providers via a single unified interface. It enables AI tools and clients to access over 20 major providers for both text and image generation, streamlining model selection and API integration. Built on FastMCP and Agno agent frameworks, it supports flexible configuration and is compatible with MCP-enabled AI tools. Authentication is provider-specific, and all interactions use a simple standardized API format.

⭐ 26
MCP
gwbischof/outsource-mcp

piapi-mcp-server

TypeScript-based MCP server for PiAPI media content generation

piapi-mcp-server is a TypeScript implementation of a Model Context Protocol (MCP) server that connects with PiAPI to enable media generation workflows from MCP-compatible applications. It handles image, video, music, TTS, 3D, and voice generation tasks using a wide range of supported models like Midjourney, Flux, Kling, LumaLabs, Udio, and more. Designed for easy integration with clients such as Claude Desktop, it includes an interactive MCP Inspector for development, testing, and debugging.

⭐ 62
MCP
apinetwork/piapi-mcp-server

@nanana-ai/mcp-server-nano-banana

MCP server for Nanana AI image generation using Gemini's nano banana model.

@nanana-ai/mcp-server-nano-banana serves as an MCP (Model Context Protocol) compatible server for facilitating image generation and transformation powered by the Gemini nano banana model. It enables clients like Claude Desktop to interact with Nanana AI, processing text prompts to generate images or transform existing images. The server can be easily configured with API tokens and integrated into desktop applications. Users can manage credentials, customize endpoints, and monitor credit usage seamlessly.

⭐ 3
MCP
nanana-app/mcp-server-nano-banana

MCP Server Giphy

MCP-compatible Giphy API server for AI models to search and retrieve GIFs.

MCP Server Giphy provides an MCP-compliant server interface for accessing GIFs from the Giphy API, specifically tailored for seamless integration with AI models. It supports content filtering, multiple retrieval methods (search, trending, random), and optimized response formats with comprehensive metadata. The server enables AI applications to search, retrieve, and utilize GIF content efficiently, and is easily configurable with tools like Claude Desktop.

⭐ 22
MCP
magarcia/mcp-server-giphy

Daisys MCP server

A beta server implementation for the Model Context Protocol supporting audio context with Daisys integration.

Daisys MCP server provides a beta implementation of the Model Context Protocol (MCP), enabling seamless integration between the Daisys AI platform and various MCP clients. It allows users to connect MCP-compatible clients to Daisys by configurable authentication and environment settings, with out-of-the-box support for audio file storage and playback. The server is designed to be extensible, including support for both user-level deployments and developer contributions, with best practices for secure authentication and dependency management.

⭐ 10
MCP
daisys-ai/daisys-mcp

Vectara MCP Server

Secure RAG server enabling seamless AI integration via Model Context Protocol.

Vectara MCP Server implements the open Model Context Protocol to enable AI systems and agentic applications to connect securely with Vectara's Trusted RAG platform. It supports multiple transport modes, including secure HTTP, Server-Sent Events (SSE), and local STDIO for development. The server provides fast, reliable retrieval-augmented generation (RAG) operations with built-in authentication, rate limiting, and optional CORS configuration. Integration is compatible with Claude Desktop and any other MCP client.

⭐ 25
MCP
vectara/vectara-mcp

View all Alternatives

Didn't find tool you were looking for?

Search AI Tools

Fal.ai MCP Server

Key Features

Use Cases

README

🎨 Fal.ai MCP Server

✨ Features

🚀 Performance

🌐 Transport Modes (New!)

🎨 Media Generation

🚀 Quick Start

Prerequisites

Installation

Option 1: Docker (Recommended for Production) 🐳

Option 2: Install from PyPI

Option 3: Install from source

Configuration

For Docker Installation:

For PyPI Installation:

For Source Installation:

💬 Usage

With Claude Desktop

HTTP/SSE Transport (New!)

📦 Supported Models

Image Models

Video Models

Audio Models

🤝 Contributing

Local Development

📝 License

🙏 Acknowledgments

Star History

Repository Owner

Repository Details

Programming Languages

Tags

Topics

Related MCPs