MCP Fal

An MCP server for interacting with fal.ai models and services

Artificial intelligence chatbots Developer tools #AI Models #Content Generation #Queue Management #File Upload .Python

rating : 2.5 points

downloads : 62

update time : 2025-04-28

What is the fal.ai MCP Server?

The fal.ai MCP server is a powerful tool that allows you to easily list, search for, and use various AI models and services provided by fal.ai. Whether you want to generate text, images, or other types of AI content, this platform can meet your needs.

How to Use the fal.ai MCP Server?

You can start using the fal.ai MCP server with just a few simple steps. First, you need to install the necessary dependencies and set up your API key. Then, you can operate the server through the command line or the web interface.

Use Cases

This server is very suitable for developers and enterprise users who want to quickly deploy AI solutions or conduct prototype development. Whether you are building a chatbot, automating content creation, or performing data analysis, the fal.ai MCP server can help you complete tasks efficiently.

Main Features

List All Available ModelsView all models provided by fal.ai in a paginated manner.

Search for Models by KeywordQuickly find relevant AI models based on keywords.

Get Model SchemaView the OpenAPI Schema of a specific model.

Generate ContentGenerate text or other forms of content using any fal.ai model.

Queue ManagementCheck the request status, get the results, and cancel queued requests.

Upload Files to fal.ai CDNUpload local files to fal.ai's Content Delivery Network (CDN).

Advantages and Limitations

Advantages

Supports multiple types of AI models and services.

Easy to integrate into existing workflows.

Provides an intuitive user interface and API.

Efficient queue management and result retrieval mechanism.

Limitations

Requires a stable internet connection to work properly.

Some advanced features may require a higher API quota.

There may be a certain learning curve for users unfamiliar with programming.

How to Use

Clone the Code Repository

Use Git to clone this project to your local environment.

Install Dependencies

Make sure you have Python 3.10+ installed and install the required Python packages.

Set the API Key

Before running, please set your fal.ai API key as an environment variable.

Start the Server

Choose a suitable way to start the server, such as development mode or direct running.

Usage Examples

Generate a Random ArticleDemonstrate how to use the fal.ai MCP server to generate a random article.

Upload an Image to CDNShow how to upload a local image to the fal.ai CDN.

Frequently Asked Questions

How can I get my fal.ai API key?

What should I do if the server fails to start?

Does it support multi - language content generation?

Related Resources

fal.ai Official Documentation

Learn more about fal.ai and its services.

GitHub Code Repository

Access the project source code and contribute.

Video Tutorial

Watch the video tutorial to learn how to use the MCP server.

🚀 fal.ai MCP Server

A Model Context Protocol (MCP) server for interacting with fal.ai models and services.

🚀 Quick Start

The fal.ai MCP Server is a powerful tool designed to facilitate seamless interaction with fal.ai models and services. It provides a range of features to manage and utilize these models effectively.

✨ Features

List all available fal.ai models.
Search for specific models based on keywords.
Retrieve the OpenAPI schema for a model.
Generate content using any fal.ai model.
Support both direct and queued model execution.
Queue management (check status, get results, cancel requests).
Upload files to the fal.ai CDN.

📦 Installation

Prerequisites

Python 3.10 or higher.
The fastmcp library.
The httpx library.
The aiofiles library.
A fal.ai API key.

Steps

Clone this repository:

git clone https://github.com/am0y/mcp-fal.git
cd mcp-fal

Install the required packages:

pip install fastmcp httpx aiofiles

Set your fal.ai API key as an environment variable:

export FAL_KEY="YOUR_FAL_API_KEY_HERE"

💻 Usage Examples

Running the Server

You can run the server in development mode:

fastmcp dev main.py

This will launch the MCP Inspector web interface, where you can test the tools.

Installation in Claude Desktop

To use the server with Claude Desktop:

fastmcp install main.py -e FAL_KEY="YOUR_FAL_API_KEY_HERE"

This will make the server available in the Desktop application.

Direct Execution

You can also run the server directly:

python main.py

📚 Documentation

Tools

models(page=None, total=None) - List all available models, supporting paginated queries.
search(keywords) - Search for models based on keywords.
schema(model_id) - Retrieve the OpenAPI schema for a specific model.
generate(model, parameters, queue=False) - Generate content using a model, with optional queued execution.
result(url) - Get the result of a queued request.
status(url) - Check the status of a queued request.
cancel(url) - Cancel a queued request.
upload(path) - Upload a file to the fal.ai CDN.