About Together AI Image Server
A TypeScript MCP server for generating images with Together AI, intended for Claude and other MCP-compatible assistants. Its `generate_image` tool accepts text prompts and returns image URLs and local paths.
Key features
- 01Generate images from text prompts
- 02Set diffusion steps
- 03Generate multiple images
- 04Return image URLs and local paths
Use cases
- 01Create images from descriptive prompts
- 02Adjust generation steps for an image
- 03Request several image variations
- 04Access generated images by URL or local path
MCP support
Exposes Together AI image generation to MCP-compatible assistants through the `generate_image` tool, which accepts a prompt and optional generation settings.
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 READMETogether AI Image Server
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A TypeScript-based MCP (Model Context Protocol) server for generating images using Together AI API.
Overview
This server provides a simple interface to generate images using Together AI's image generation models through the MCP protocol. It allows Claude and other MCP-compatible assistants to generate images based on text prompts.
Features
Tools
generate_image- Generate images from text prompts- Takes a text prompt as required parameter
- Optional parameters for controlling generation steps and number of images
- Returns URLs and local paths to generated images
Prerequisites
- Node.js (v14 or later recommended)
- Together AI API key
Installation
# Clone the repository
git clone https://github.com/zym9863/together-ai-image-server.git
cd together-ai-image-server
# Install dependencies
npm install
Configuration
Set your Together AI API key as an environment variable:
# On Linux/macOS
export TOGETHER_API_KEY="your-api-key-here"
# On Windows (Command Prompt)
set TOGETHER_API_KEY=your-api-key-here
# On Windows (PowerShell)
$env:TOGETHER_API_KEY="your-api-key-here"
Alternatively, you can create a .env file in the project root:
TOGETHER_API_KEY=your-api-key-here
Development
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Usage with Claude Desktop
To use with Claude Desktop, add the server config:
On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"Together AI Image Server": {
"command": "/path/to/together-ai-image-server/build/index.js"
}
}
}
Replace /path/to/together-ai-image-server with the actual path to your installation.
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
API Reference
generate_image
Generates images based on a text prompt using Together AI's image generation API.
Parameters:
prompt(string, required): Text prompt for image generationsteps(number, optional, default: 4): Number of diffusion steps (1-4)n(number, optional, default: 1): Number of images to generate (1-4)
Returns:
JSON object containing:
image_urls: Array of URLs to the generated imageslocal_paths: Array of paths to locally cached images
License
MIT
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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.