Azure Image Generation

Azure Image generation MCP

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6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "malikmalikayesha-azure-image-generation-mcp": {
      "command": "node",
      "args": [
        "/path/to/azure-image-generation-server.js"
      ],
      "env": {
        "AZURE_IMAGE_API_KEY": "${AZURE_IMAGE_API_KEY}",
        "AZURE_IMAGE_BASE_URL": "${AZURE_IMAGE_BASE_URL}"
      }
    }
  }
}

This MCP server enables AI-powered image generation within LibreChat by routing requests to Azure OpenAI's DALL-E 3 and FLUX models. It automatically selects the most suitable model based on your prompts and offers multiple image sizes and customization options to help you create photorealistic or creative images directly in chat.

How to use

You interact with the Image Generation MCP just like any other tool in your LibreChat environment. Describe the scene you want, and the server will generate an image using either DALL-E 3 for photorealistic results or FLUX for creative illustrations. You can rely on automatic model selection, or explicitly request a specific model by mentioning its name in your prompt.

How to install

Prerequisites: ensure you have Node.js version 18 or newer installed on your system.

Option A: Install the MCP server globally (recommended for quick setup)

npm install -g azure-image-generation-mcp

Option B: Install from source

git clone https://github.com/malikmalikayesha/azure-image-generation-mcp.git
cd azure-image-generation-mcp
npm install

Option C: Run via NPX (no installation)

npx azure-image-generation-mcp

Additional configuration and notes

Configure environment variables in your environment or a .env file to enable Azure authentication and endpoint usage.

Configuration for LibreChat integration

In your LibreChat setup, declare the MCP server so the client can communicate with it. The following configuration illustrates how to reference the local server binary and set necessary timeouts and environment variables.

Usage examples and prompts

Ask for specific image results by describing your scene. Examples include photorealistic portraits, landscapes, and creative patterns. You can also specify size and style preferences in your prompts to influence the output.

Model and size options

The server supports multiple image sizes (1024x1024, 1792x1024, 1024x1792) and allows you to influence quality and style through prompts. The system automatically selects between DALL-E 3 and FLUX unless you explicitly request a model in your prompt.

Advanced usage tips

For rapid iterations, describe concise prompts and iterate on style and size keywords. If you need higher resolution or particular composition, specify those requirements in your prompt so the MCP can adjust the generation parameters accordingly.

Troubleshooting basics

If images do not render properly in LibreChat, verify your LibreChat version includes the MCP image rendering fix and confirm the MCP integration is correctly referenced in your chat configuration.

Security and access

Safeguard your Azure API key and base URL. Do not expose keys in public code or logs. Use environment separation for development and production deployments.

Notes on usage limits

Azure OpenAI quotas and limits apply to DALL-E 3 and FLUX usage. Monitor usage to avoid interruptions during peak activity.

Available tools

generate_image

Generates an AI image based on a text prompt, returning a description, base64 image data, and metadata about the model, size, and generation time.