Together AI Image Server
The Together AI Image Server allows you to generate images from text prompts using Together AI's API. With this server, you can:
Generate Images: Create images based on text descriptions
Control Output: Specify the number of images (1-4) and diffusion steps (1-4)
Receive Results: Get URLs and local paths to the generated images
Integration: Works as an MCP server, compatible with MCP-compatible assistants like Claude Desktop
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Together AI Image Server generate an image of a futuristic city at sunset with flying cars"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Together 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.
Related MCP server: gpt-mcp
Features
Tools
generate_image- Generate images from text promptsTakes 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 installConfiguration
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-hereDevelopment
Build the server:
npm run buildFor development with auto-rebuild:
npm run watchUsage 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 inspectorThe 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.
Available Tools
1 toolgenerate_imageC
Generate image from text prompt using Together AI API
Inputs: prompt (required), n, steps.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly defined.
The single tool 'generate_image' follows a clear verb_noun pattern, which is consistent by default.
The server has only one tool, which is too few for a typical image generation service. Users would likely expect additional tools for model selection, image variants, or status retrieval.
The tool surface is severely incomplete; a comprehensive image generation server would typically include tools for listing models, configuring generation parameters, and possibly managing generated images.
Maintenance
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