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Together AI Image MCP Server

Together AI Image MCP Server

by stefanskiasan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Together AI Image Server

An MCP server for generating images using Together AI's image generation models.

Setup

  1. Install dependencies:

npm install

  1. Build the server:

npm run build

Related MCP server: openrouter-image-gen-mcp

Configuration

1. Together AI API Key

The server requires a Together AI API key. You can get one from Together AI's platform.

2. Cline Configuration

Add the server to your Cline MCP settings file:

For macOS/Linux: ~/Library/Application Support/Windsurf/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

{
  "mcpServers": {
    "togetherai-image": {
      "command": "node",
      "args": ["/path/to/togetherai-image-server/build/index.js"],
      "env": {
        "TOGETHER_API_KEY": "your-api-key-here"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Usage in Cline

The server provides a generate_image tool with the following parameters:

{
  prompt: string;           // Required: Text description of the image to generate
  model?: string;          // Optional: Model to use (default: 'black-forest-labs/FLUX.1.1-pro')
  width?: number;          // Optional: Image width in pixels (default: 1024)
  height?: number;         // Optional: Image height in pixels (default: 768)
  steps?: number;         // Optional: Number of inference steps (default: 28)
  n?: number;             // Optional: Number of images to generate (default: 1)
  outputDir?: string;     // Optional: Directory where images will be saved (default: './output')
}

Example Usage

You can use the server in Cline like this:

Generate an image of a cat and save it to my desktop:

<use_mcp_tool>
<server_name>togeherai-image</server_name>
<tool_name>generate_image</tool_name>
<arguments>
{
  "prompt": "A cute cat sitting on a windowsill",
  "outputDir": "/Users/username/Desktop/generated-images"
}
</arguments>
</use_mcp_tool>

Output

The tool returns a JSON response containing:

  • filepath: Full path to the saved image

  • filename: Name of the saved image file

  • dimensions: Original and final dimensions of the image

Features

  • Supports Together AI's latest FLUX.1.1-pro model

  • Automatically resizes images if dimensions are below 256 pixels

  • Maintains aspect ratio during resizing

  • High-quality JPEG output (90% quality)

  • Creates output directories recursively

  • Returns detailed metadata including image dimensions

Available Tools

1 tool
generate_imageC

Generate an image using Together AI

Inputs: prompt (required), model, width, height, +4 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.1/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate_image' has a clear and distinct purpose, making it impossible for an agent to misselect between non-existent alternatives.

    Naming Consistency5/5

    The naming pattern cannot be inconsistent with only one tool. The tool name 'generate_image' follows a verb_noun convention, which is straightforward and predictable, though there are no other tools to compare it against for consistency.

    Tool Count2/5

    A single tool for an image generation server feels thin and under-scoped. While it covers the core functionality, typical image generation APIs offer more operations (e.g., variations, edits, or style transfers), making this count borderline too few for the apparent domain.

    Completeness2/5

    The tool set is severely incomplete for an image generation domain. It only provides generation, with no obvious gaps to assess since there are no other tools, but the lack of common operations like editing, upscaling, or batch processing suggests significant coverage issues for agent workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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