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openai-gpt-image-mcp

openai-gpt-image-mcp

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github.com/SureScaleAIAI & Agents118Updated 74w ago

About openai-gpt-image-mcp

openai-gpt-image-mcp is an MCP tool server that wraps OpenAI's GPT-4o and gpt-image-1 image generation and editing APIs. It suits users who want to generate or modify images from within MCP-compatible clients. Results larger than 1MB are saved to disk automatically.

Key features

  1. 01Generate images from text prompts
  2. 02Edit or extend images with prompts and optional masks
  3. 03Accept file paths or base64 input
  4. 04Save output to disk or return base64
  5. 05Generate up to 10 images per request

Use cases

  1. 01Creating illustrations from Claude Desktop or Cursor
  2. 02Inpainting or extending existing images
  3. 03Batch generating related images and saving them locally

MCP support

This project is an MCP server that exposes the create-image and edit-image tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

openai-gpt-image-mcp

MCP SDK OpenAI SDK License GitHub stars Build Status


A Model Context Protocol (MCP) tool server for OpenAI's GPT-4o/gpt-image-1 image generation and editing APIs.

  • Generate images from text prompts using OpenAI's latest models.
  • Edit images (inpainting, outpainting, compositing) with advanced prompt control.
  • Supports: Claude Desktop, Cursor, VSCode, Windsurf, and any MCP-compatible client.

✨ Features

  • create-image: Generate images from a prompt, with advanced options (size, quality, background, etc).
  • edit-image: Edit or extend images using a prompt and optional mask, supporting both file paths and base64 input.
  • File output: Save generated images directly to disk, or receive as base64.

🚀 Installation

git clone https://github.com/SureScaleAI/openai-gpt-image-mcp.git
cd openai-gpt-image-mcp
yarn install
yarn build

🔑 Configuration

Add to Claude Desktop or VSCode (including Cursor/Windsurf) config:

{
  "mcpServers": {
    "openai-gpt-image-mcp": {
      "command": "node",
      "args": ["/absolute/path/to/dist/index.js"],
      "env": { "OPENAI_API_KEY": "sk-..." }
    }
  }
}

Also supports Azure deployments:

{
  "mcpServers": {
    "openai-gpt-image-mcp": {
      "command": "node",
      "args": ["/absolute/path/to/dist/index.js"],
      "env": { 
        "AZURE_OPENAI_API_KEY": "sk-...",
        "AZURE_OPENAI_ENDPOINT": "my.endpoint.com",
        "OPENAI_API_VERSION": "2024-12-01-preview"
      }
    }
  }
}

Also supports supplying an environment files:

{
  "mcpServers": {
    "openai-gpt-image-mcp": {
      "command": "node",
      "args": ["/absolute/path/to/dist/index.js", "--env-file", "./deployment/.env"]
    }
  }
}

⚡ Advanced

  • For create-image, set n to generate up to 10 images at once.
  • For edit-image, provide a mask image (file path or base64) to control where edits are applied.
  • Provide an environment file with --env-file path/to/file/.env
  • See src/index.ts for all options.

🧑‍💻 Development

  • TypeScript source: src/index.ts
  • Build: yarn build
  • Run: node dist/index.js

📝 License

MIT


🩺 Troubleshooting

  • Make sure your OPENAI_API_KEY is valid and has image API access.
  • You must have a verified OpenAI organization. After verifying, it can take 15–20 minutes for image API access to activate.
  • File paths must be absolute.
    • Unix/macOS/Linux: Starting with / (e.g., /path/to/image.png)
    • Windows: Drive letter followed by : (e.g., C:/path/to/image.png or C:\path\to\image.png)
  • For file output, ensure the directory is writable.
  • If you see errors about file types, check your image file extensions and formats.

⚠️ Limitations & Large File Handling

  • 1MB Payload Limit: MCP clients (including Claude Desktop) have a hard 1MB limit for tool responses. Large images (especially high-res or multiple images) can easily exceed this limit if returned as base64.
  • Auto-Switch to File Output: If the total image size exceeds 1MB, the tool will automatically save images to disk and return the file path(s) instead of base64. This ensures compatibility and prevents errors like result exceeds maximum length of 1048576.
  • Default File Location: If you do not specify a file_output path, images will be saved to /tmp (or the directory set by the MCP_HF_WORK_DIR environment variable) with a unique filename.
  • Environment Variable:
    • MCP_HF_WORK_DIR: Set this to control where large images and file outputs are saved. Example: export MCP_HF_WORK_DIR=/your/desired/dir
  • Best Practice: For large or production images, always use file output and ensure your client is configured to handle file paths.

📚 References


🙏 Credits

Comments

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From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.