GPT Image Generator

Name: GPT Image Generator
Rating: 4.4 (37 reviews)
Author: cloudwerx-dev

Connects to OpenAI's gpt-image-1 model to generate and edit images from text prompts, file paths, or base64 inputs. Provides direct image creation capabilities through the Model Context Protocol.

Enables direct image generation and editing through OpenAI's gpt-image-1 model with support for text prompts, file paths, and base64 encoded inputs for creative workflows and visual content creation.

18393 views8Local (stdio)

ai ml

GitHub

What it does

Generate images from text descriptions
Edit existing images with prompts
Process base64 encoded image inputs
Handle image files from local paths
Create visual content on demand

Best for

Content creators needing quick image generationDevelopers building AI-powered apps with visualsCreative workflows requiring automated image editing

Uses OpenAI's gpt-image-1 modelMultiple input formats supportedNPX ready - no installation needed

About GPT Image Generator

GPT Image Generator is a community-built MCP server published by cloudwerx-dev that provides AI assistants with tools and capabilities via the Model Context Protocol. Generate and edit images instantly using GPT Image Generator, an advanced AI image generator for creative visual content It is categorized under ai ml.

How to install

You can install GPT Image Generator in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

GPT Image Generator is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

@cloudwerxlab/gpt-image-1-mcp

A Model Context Protocol (MCP) server for generating and editing images using the OpenAI gpt-image-1 model.

🚀 Quick Start

Run this MCP server directly using NPX without installing it. View on npm.

npx -y @cloudwerxlab/gpt-image-1-mcp

The -y flag automatically answers "yes" to any prompts that might appear during the installation process.

📋 Prerequisites

Node.js (v14 or higher)

OpenAI API key with access to gpt-image-1

🔑 Environment Variables

Variable	Required	Description
`OPENAI_API_KEY`	✅ Yes	Your OpenAI API key with access to the gpt-image-1 model
`GPT_IMAGE_OUTPUT_DIR`	❌ No	Custom directory for saving generated images (defaults to user's Pictures folder under `gpt-image-1` subfolder)

💻 Example Usage with NPX

Operating System Command Line Example

Linux/macOS

# Set your OpenAI API key
export OPENAI_API_KEY=sk-your-openai-api-key

# Optional: Set custom output directory
export GPT_IMAGE_OUTPUT_DIR=/home/username/Pictures/ai-generated-images

# Run the server with NPX
npx -y @cloudwerxlab/gpt-image-1-mcp

Windows (PowerShell)

# Set your OpenAI API key
$env:OPENAI_API_KEY = "sk-your-openai-api-key"

# Optional: Set custom output directory
$env:GPT_IMAGE_OUTPUT_DIR = "C:\Users\username\Pictures\ai-generated-images"

# Run the server with NPX
npx -y @cloudwerxlab/gpt-image-1-mcp

Windows (Command Prompt)

:: Set your OpenAI API key
set OPENAI_API_KEY=sk-your-openai-api-key

:: Optional: Set custom output directory
set GPT_IMAGE_OUTPUT_DIR=C:\Users\username\Pictures\ai-generated-images

:: Run the server with NPX
npx -y @cloudwerxlab/gpt-image-1-mcp

🔌 Integration with MCP Clients

🛠️ Setting Up in an MCP Client

Step 1: Locate Settings File

For Roo: c:\Users\<username>\AppData\Roaming\Code\User\globalStorage\rooveterinaryinc.roo-cline\settings\mcp_settings.json
For VS Code MCP Extension: Check your extension documentation for the settings file location
For Cursor: ~/.config/cursor/mcp_settings.json (Linux/macOS) or %APPDATA%\Cursor\mcp_settings.json (Windows)
For Augment: ~/.config/augment/mcp_settings.json (Linux/macOS) or %APPDATA%\Augment\mcp_settings.json (Windows)
For Windsurf: ~/.config/windsurf/mcp_settings.json (Linux/macOS) or %APPDATA%\Windsurf\mcp_settings.json (Windows)

Step 2: Add Configuration

Add the following configuration to the mcpServers object:

{
  "mcpServers": {
    "gpt-image-1": {
      "command": "npx",
      "args": [
        "-y",
        "@cloudwerxlab/gpt-image-1-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "PASTE YOUR OPEN-AI KEY HERE",
        "GPT_IMAGE_OUTPUT_DIR": "OPTIONAL: PATH TO SAVE GENERATED IMAGES"
      }
    }
  }
}

Example Configurations for Different Operating Systems

Operating System Example Configuration

Windows

{
  "mcpServers": {
    "gpt-image-1": {
      "command": "npx",
      "args": ["-y", "@cloudwerxlab/gpt-image-1-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-your-openai-api-key",
        "GPT_IMAGE_OUTPUT_DIR": "C:\\Users\\username\\Pictures\\ai-generated-images"
      }
    }
  }
}

Linux/macOS

{
  "mcpServers": {
    "gpt-image-1": {
      "command": "npx",
      "args": ["-y", "@cloudwerxlab/gpt-image-1-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-your-openai-api-key",
        "GPT_IMAGE_OUTPUT_DIR": "/home/username/Pictures/ai-generated-images"
      }
    }
  }
}

Note: For Windows paths, use double backslashes (\\) to escape the backslash character in JSON. For Linux/macOS, use forward slashes (/).

✨ Features

🎨 Core Tools

create_image: Generate new images from text prompts
create_image_edit: Edit existing images with text prompts and masks

🚀 Key Benefits

Simple integration with MCP clients
Full access to OpenAI's gpt-image-1 capabilities
Streamlined workflow for AI image generation

💡 Enhanced Capabilities

📊 Output & Formatting

✅ Beautifully Formatted Output: Responses include emojis and detailed information
✅ Automatic Image Saving: All generated images saved to disk for easy access
✅ Detailed Token Usage: View token consumption for each request

⚙️ Configuration & Handling

✅ Configurable Output Directory: Customize where images are saved
✅ File Path Support: Edit images using file paths instead of base64 encoding
✅ Comprehensive Error Handling: Detailed error reporting with specific error codes, descriptions, and troubleshooting suggestions

🔄 How It Works

🖼️ Image Generation	✏️ Image Editing
Server receives prompt and parameters Calls OpenAI API using gpt-image-1 model API returns base64-encoded images Server saves images to configured directory Returns formatted response with paths and metadata	Server receives image, prompt, and optional mask For file paths, reads and prepares files for API Uses direct curl command for proper MIME handling API returns base64-encoded edited images Server saves images to configured directory Returns formatted response with paths and metadata

📁 Output Directory Behavior

📂 Storage Location

🔹 Default Location: User's Pictures folder under gpt-image-1 subfolder (e.g., C:\Users\username\Pictures\gpt-image-1 on Windows)
🔹 Custom Location: Set via GPT_IMAGE_O README truncated. View full README on GitHub.

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