Together AI Image Server
A TypeScript-based server for generating images using the Together AI API.
Together AI Image Server
English | 简体中文
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.
Related Servers
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Code Context Provider MCP
Provides code context and analysis for AI assistants using WebAssembly Tree-sitter parsers.
limelink-mcp-server
MCP server for managing Limelink dynamic links with platform-specific deep linking (iOS/Android), social previews, and UTM tracking
iOS Device Control
An MCP server to control iOS simulators and real devices, enabling AI assistant integration on macOS.
Flutter MCP
Provides real-time Flutter/Dart documentation and pub.dev package information to AI assistants, supporting all packages on demand.
BrandKity MCP
Build entire brand kits with a single prompt
Bio-MCP FastQC Server
Provides quality control for biological sequence data using the FastQC and MultiQC tools.
FleetQ
AI Agent Mission Control — 200+ MCP tools for managing agents, experiments, workflows, crews, skills, approvals, budgets, and more.
Metasploit MCP Server
An MCP server for integrating with the Metasploit Framework, enabling payload generation and management.
ToolPipe MCP Server
145+ developer tools via MCP: JSON, QR codes, DNS, hash, UUID, JWT, SQL formatter, and more
Accordo MCP Server
Provides dynamic YAML-driven workflow guidance for AI coding agents with structured development workflows, progression control, and decision points.