About Image Generation MCP Server
A Python MCP server that generates images from text prompts through Together AI’s Flux.1 Schnell model. It is for users who want image generation in MCP-compatible clients, with optional width and height settings.
Key features
- 01Generate images with Flux.1 Schnell
- 02Create images from text prompts
- 03Set custom image dimensions
- 04Handle prompt validation and API errors
Use cases
- 01Generate images from descriptions
- 02Specify output image dimensions
- 03Use image generation in MCP clients
MCP support
The server exposes a `generate_image` tool to MCP-compatible clients, accepting a text prompt and optional width and height.
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 READMEImage Generation MCP Server
A Model Context Protocol (MCP) server that enables seamless generation of high-quality images via Together AI. This server provides a standardized interface to specify image generation parameters.
Features
- High-quality image generation powered by the Flux.1 Schnell model
- Support for customizable dimensions (width and height)
- Clear error handling for prompt validation and API issues
- Easy integration with MCP-compatible clients
Installation
Claude Desktop
- On MacOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json - On Windows:
%APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"image-gen": {
"command": "uv",
"args": ["--directory", "/ABSOLUTE/PATH/TO/image-gen/", "run", "image-gen"],
"env": {
"TOGETHER_AI_API_KEY": "<API KEY>"
}
}
}
}
Available Tools
The server implements one tool:
generate_image
Generates an image based on the given textual prompt and optional dimensions.
Input Schema:
{
"prompt": {
"type": "string",
"description": "A descriptive prompt for generating the image (e.g., 'a futuristic cityscape at sunset')"
},
"width": {
"type": "integer",
"description": "Width of the generated image in pixels (optional)"
},
"height": {
"type": "integer",
"description": "Height of the generated image in pixels (optional)"
},
"model": {
"type": "string",
"description": "The exact model name as it appears in Together AI. If incorrect, it will fallback to the default model (black-forest-labs/FLUX.1-schnell)."
}
}
Prerequisites
- Python 3.12 or higher
- httpx
- mcp
Contributing
Contributions are welcome! Please follow these steps to contribute:
- Fork the repository
- Create a new branch (
feature/my-new-feature) - Commit your changes
- Push the branch to your fork
- Open a Pull Request
For significant changes, please open an issue first to discuss your proposed changes.
License
This project is licensed under the MIT License. See the LICENSE file for details.
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.