About Flux ImageGen MCP Server
Flux ImageGen MCP Server exposes image generation functions powered by Pollinations AI. It is for MCP clients that need to create image URLs or save generated images, and can list available models.
Key features
- 01Generates images from text prompts
- 02Creates image URLs
- 03Saves generated images to a path
- 04Lists available image models
- 05Configurable dimensions and options
Use cases
- 01Generating images from a text prompt
- 02Saving generated images to a specified location
MCP support
The MCP server exposes tools for generating image URLs, generating and saving images, and listing available image models.
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 READMEFlux ImageGen MCP Server
A specialized Model Context Protocol (MCP) server for image generation and manipulation, powered by Pollinations AI.
Developer
- Author: Falah.G.Salieh
- Copyright: © 2025 All rights reserved
Overview
ImageGen MCP Server is a streamlined server implementation that provides powerful image generation capabilities through the Model Context Protocol (MCP). This server specializes in three core functionalities:
- Image URL Generation
- Direct Image Generation
- Model Listing and Management
Features
- 🖼️ Image Generation: Create stunning images from text prompts
- 🎨 Multiple Models: Support for various image generation models
- 🔧 Flexible Configuration: Easy to set up and customize
- 🚀 High Performance: Optimized for quick response times
- 🔄 MCP Compatible: Fully compliant with Model Context Protocol
Installation
# Clone the repository
git clone https://github.com/yourusername/flux-imagegen-mcp-server.git
# Install dependencies
npm install
Configuration
Claude Desktop Configuration
To use this server with Claude Desktop, update your configuration file at:
C:\Users\[YourUsername]\AppData\Roaming\Claude\claude_desktop_config.json
{
"mcpServers": {
"mcpollinations": {
"command": "cmd",
"args": [
"/c",
"node",
"PATH_TO_YOUR_SERVER\\server.js"
],
"tools": [
"generateImageUrl",
"generateImage",
"listImageModels"
]
}
}
}
Replace PATH_TO_YOUR_SERVER with your actual server path.
Available Tools
1. Generate Image URL (generateImageUrl)
Generates a URL for an image based on a text prompt.
{
"prompt": "A beautiful sunset over mountains",
"model": "flux", // optional, defaults to 'flux'
"width": 1024, // optional
"height": 1024, // optional
"enhance": true, // optional
"safe": false // optional
}
2. Generate Image (generateImage)
Generates and saves an image directly from a text prompt.
{
"prompt": "A serene lake reflecting mountains",
"model": "flux",
"width": 1024,
"height": 1024,
"enhance": true,
"safe": false,
"outputPath": "./output",
"fileName": "mountain_lake",
"format": "png"
}
3. List Image Models (listImageModels)
Returns a list of available image generation models.
// Example response:
{
"models": [
{
"id": "flux",
"name": "Flux",
"description": "Default image generation model"
},
// ... other models
]
}
Running the Server
# Start the server
node server.js
Environment Requirements
- Node.js >= 16.0.0
- NPM >= 7.0.0
- Windows/Linux/MacOS compatible
Development
To contribute or modify the server:
- Fork the repository
- Create your feature branch
- Make your changes
- Submit a pull request
Error Handling
The server provides detailed error messages for common issues:
{
"error": {
"code": "ERROR_CODE",
"message": "Human-readable error message",
"details": { /* Additional error details */ }
}
}
Examples
Basic Image Generation
// Generate an image URL
const response = await generateImageUrl({
prompt: "A futuristic city at night",
model: "flux",
width: 1024,
height: 1024
});
// Generate and save an image
const image = await generateImage({
prompt: "A peaceful garden with butterflies",
outputPath: "./images",
fileName: "garden_scene"
});
Download Image Example
// Download an image from URL
const downloadResult = await downloadImage({
imageUrl: "https://example.com/image.jpg",
fileName: "downloaded-image",
format: "png"
});
Support
For issues and feature requests, please create an issue in the repository or contact the developer:
- Email: [Your contact email]
- GitHub: [Your GitHub profile]
License
This project is licensed under the MIT License - see the LICENSE file for details.
Made with ❤️ by Falah.G.Salieh © 2025 All rights reserved
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.