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.
관련 서버
Scout Monitoring MCP
스폰서Put performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
스폰서Access financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Binalyze AIR MCP Server
Interact with Binalyze AIR's digital forensics and incident response capabilities using natural language.
OpenRouter MCP Client for Cursor
An MCP client for Cursor that uses OpenRouter.ai to access multiple AI models. Requires an OpenRouter API key.
MCP Rules Enforcer Zero
An MCP server that enforces rules from markdown files for AI agents. This is a zero-tool version that requires an external rules file.
WordPress MCP
A Python MCP server for interacting with a local WordPress instance.
Scorecard
Access Scorecard's AI model evaluation and testing tools via a Cloudflare Workers deployment.
Tecton
Feature engineering assistance using the Tecton platform, integrated with Cursor.
AWS CDK MCP Server
Offers guidance and tools for AWS CDK, covering best practices, security compliance with CDK Nag, infrastructure validation, and pattern discovery.
Remote MCP Server (Authless)
An example of a remote MCP server without authentication, deployable on Cloudflare Workers.
MCP Hangar
Kubernetes-native registry for managing multiple MCP servers with lazy loading, health monitoring, and RBAC
SCMCP
A natural language interface for single-cell RNA sequencing (scRNA-Seq) analysis, supporting various modules from IO to enrichment.