Image Generation MCP Server
About
MCP server enabling high-quality image generation via Together AI's Flux.1 Schnell model.
Details
- Author
- manascb1344
- GitHub stars
- 9
- Downloads
- 435
- Categories
- Media
Jump to
- High-quality image generation using the Flux.1 Schnell model
- Customizable dimensions (width and height)
- Clear error handling for prompt validation and API issues
- Easy integration with MCP‑compatible clients
- Optional image saving to disk as PNG
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Image Generation MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install the package with npm install together-mcp or run directly with npx together-mcp@latest. Configure the server by adding it to your MCP configuration with your Together AI API key. Then invoke the generate_image tool with a required text prompt and optional parameters.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"image generation mcp server": {
"together-mcp-server": {
"command": "npx",
"args": [
"together-mcp@latest"
]
}
}
}
}
McpServers
{
"together-mcp-server": {
"command": "npx",
"args": [
"together-mcp@latest"
]
}
}
Image Generation MCP Server
A Model Context Protocol (MCP) server that enables seamless generation of high-quality images using the Flux.1 Schnell model via Together AI. This server provides a standardized interface to specify image generation parameters.
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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
- Optional image saving to disk in PNG format
Installation
npm install together-mcp
Or run directly:
npx together-mcp@latest
Configuration
Add to your MCP server configuration:
<summary>Configuration Example</summary>
{
"mcpServers": {
"together-image-gen": {
"command": "npx",
"args": ["together-mcp@latest -y"],
"env": {
"TOGETHER_API_KEY": "<API KEY>"
}
}
}
}
Usage
The server provides one tool: generate_image
Using generate_image
This tool has only one required parameter - the prompt. All other parameters are optional and use sensible defaults if not provided.
Parameters
{
// Required
prompt: string; // Text description of the image to generate
// Optional with defaults
model?: string; // Default: "black-forest-labs/FLUX.1-schnell-Free"
width?: number; // Default: 1024 (min: 128, max: 2048)
height?: number; // Default: 768 (min: 128, max: 2048)
steps?: number; // Default: 1 (min: 1, max: 100)
n?: number; // Default: 1 (max: 4)
response_format?: string; // Default: "b64_json" (options: ["b64_json", "url"])
image_path?: string; // Optional: Path to save the generated image as PNG
}
Minimal Request Example
Only the prompt is required:
{
"name": "generate_image",
"arguments": {
"prompt": "A serene mountain landscape at sunset"
}
}
Full Request Example with Image Saving
Override any defaults and specify a path to save the image:
{
"name": "generate_image",
"arguments": {
"prompt": "A serene mountain landscape at sunset",
"width": 1024,
"height": 768,
"steps": 20,
"n": 1,
"response_format": "b64_json",
"model": "black-forest-labs/FLUX.1-schnell-Free",
"image_path": "/path/to/save/image.png"
}
}
Response Format
The response will be a JSON object containing:
{
"id": string, // Generation ID
"model": string, // Model used
"object": "list",
"data": [
{
"timings": {
"inference": number // Time taken for inference
},
"index": number, // Image index
"b64_json": string // Base64 encoded image data (if response_format is "b64_json")
// OR
"url": string // URL to generated image (if response_format is "url")
}
]
}
If image_path was provided and the save was successful, the response will include confirmation of the save location.
Default Values
If not specified in the request, these defaults are used:
- model: "black-forest-labs/FLUX.1-schnell-Free"
- width: 1024
- height: 768
- steps: 1
- n: 1
- response_format: "b64_json"
Important Notes
1. Only the prompt parameter is required
2. All optional parameters use defaults if not provided
3. When provided, parameters must meet their constraints (e.g., width/height ranges)
4. Base64 responses can be large - use URL format for larger images
5. When saving images, ensure the specified directory exists and is writable
Prerequisites
- Node.js >= 16
- Together AI API key
1. Sign in at api.together.xyz
2. Navigate to API Keys settings
3. Click "Create" to generate a new API key
4. Copy the generated key for use in your MCP configuration
Dependencies
{
"@modelcontextprotocol/sdk": "0.6.0",
"axios": "^1.6.7"
}
Development
Clone and build the project:
git clone https://github.com/manascb1344/together-mcp-server
cd together-mcp-server
npm install
npm run build
Available Scripts
- npm run build - Build the TypeScript project
- npm run watch - Watch for changes and rebuild
- npm run inspector - Run MCP inspector
Contributing
Contributions are welcome! Please follow these steps:
1. Fork the repository
2. Create a new branch (feature/my-new-feature)
3. Commit your changes
4. Push the branch to your fork
5. Open a Pull Request
Feature requests and bug reports can be submitted via GitHub Issues. Please check existing issues before creating a new one.
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.
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