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Together Mcp Server
What is Together Mcp Server
together-mcp-server is a Model Context Protocol (MCP) server that facilitates the generation of high-quality images using Together AI’s Flux.1 Schnell model. It provides a standardized interface for specifying image generation parameters.
Use cases
Use cases for together-mcp-server include generating images for creative projects, visual content creation for marketing, and developing applications that require dynamic image generation based on user input.
How to use
To use together-mcp-server, install it via npm with the command ‘npm install together-mcp’ or run it directly using ‘npx together-mcp@latest’. Configure the server by adding it to your MCP server configuration and use the ‘generate_image’ tool with the required prompt parameter.
Key features
Key features include high-quality image generation, customizable dimensions (width and height), clear error handling for prompt validation, easy integration with MCP-compatible clients, and optional image saving in PNG format.
Where to use
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Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Together Mcp Server
together-mcp-server is a Model Context Protocol (MCP) server that facilitates the generation of high-quality images using Together AI’s Flux.1 Schnell model. It provides a standardized interface for specifying image generation parameters.
Use cases
Use cases for together-mcp-server include generating images for creative projects, visual content creation for marketing, and developing applications that require dynamic image generation based on user input.
How to use
To use together-mcp-server, install it via npm with the command ‘npm install together-mcp’ or run it directly using ‘npx together-mcp@latest’. Configure the server by adding it to your MCP server configuration and use the ‘generate_image’ tool with the required prompt parameter.
Key features
Key features include high-quality image generation, customizable dimensions (width and height), clear error handling for prompt validation, easy integration with MCP-compatible clients, and optional image saving in PNG format.
Where to use
undefined
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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.
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:
{
"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:
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
- Only the
promptparameter is required - All optional parameters use defaults if not provided
- When provided, parameters must meet their constraints (e.g., width/height ranges)
- Base64 responses can be large - use URL format for larger images
- When saving images, ensure the specified directory exists and is writable
Prerequisites
- Node.js >= 16
- Together AI API key
- Sign in at api.together.xyz
- Navigate to API Keys settings
- Click “Create” to generate a new API key
- 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 projectnpm run watch- Watch for changes and rebuildnpm run inspector- Run MCP inspector
Contributing
Contributions are welcome! Please follow these steps:
- Fork the repository
- Create a new branch (
feature/my-new-feature) - Commit your changes
- Push the branch to your fork
- 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.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










