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Together AI Image Server

Together AI Image Server

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github.com/zym9863Media & Design4Updated 32w ago

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

  1. 01Generate images from text prompts
  2. 02Set diffusion steps
  3. 03Generate multiple images
  4. 04Return image URLs and local paths

Use cases

  1. 01Create images from descriptive prompts
  2. 02Adjust generation steps for an image
  3. 03Request several image variations
  4. 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.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Together AI Image Server

English | 简体中文

A TypeScript-based MCP (Model Context Protocol) server for generating images using Together AI API.

Together AI Image Server MCP server

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 generation
  • steps (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 images
  • local_paths: Array of paths to locally cached images

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Comments

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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.