Together AI Image Server MCP Server

@zym9863

Repository

Basic information

About Together AI Image Server MCP Server

The server acts as a bridge between MCP-compatible assistants and Together AI's image generation capabilities.

Together AI Image Server MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Together AI Image Server MCP Server tools

Generate images from text prompts

Overview

What is Together AI Image Server?

Together AI Image Server is a TypeScript-based MCP (Model Context Protocol) server that generates images using the Together AI API. It provides a simple interface for Claude and other MCP-compatible assistants to create images from text prompts.

How to use Together AI Image Server?

Install the server by cloning the repository and running npm install. Set the TOGETHER_API_KEY environment variable or create a .env file with your Together AI API key. Build the server with npm run build, then configure Claude Desktop by adding the path to the built index.js in the mcpServers section of the Claude Desktop configuration file.

Key features of Together AI Image Server

Exposes a generate_image tool for text-to-image generation
Requires only a text prompt; optional steps (1-4) and number of images (1-4)
Returns image URLs and local file paths
Built with TypeScript for reliable MCP integration
Debug using the MCP Inspector via npm run inspector

Use cases of Together AI Image Server

Generate images directly from Claude Desktop conversations
Create multiple image variations from a single prompt
Cache generated images locally for later use
Integrate image generation into any MCP-compatible workflow

Frequently asked questions

What runtime and API key are required?

Node.js v14 or later and a Together AI API key are required. The API key is set as the environment variable `TOGETHER_API_KEY` or in a `.env` file.

Where are generated images stored?

The server returns URLs to the images and saves local copies to paths reported in the response.

What are the limits for image generation?

The `steps` parameter accepts 1–4 diffusion steps (default 4), and the `n` parameter accepts 1–4 images (default 1).

How does the server communicate with clients?

The server uses the MCP protocol over standard I/O (stdio), as is typical for MCP servers.

How can I debug the server?

Use the MCP Inspector by running `npm run inspector`, which provides a URL for browser-based debugging tools.

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