Which integrations are available for this server?

Allows downloading toy-related images from DuckDuckGo search results.

How do I use MCP Image Tools Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Image Tools Server fetch 5 toy robot images to ./images" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Image Tools Server

by tcalecchen

Overview Schema Source Related Servers Discussions Admin

Python

Local

MCP Image Tools Server

A Model Context Protocol (MCP) server that provides powerful image processing tools for Claude Code. This server implements three main functionalities: downloading toy-related images from the web, resizing images, and removing backgrounds from images.

Anthropic MCP Pythone SDK Github repo: https://github.com/modelcontextprotocol/python-sdk?tab=readme-ov-file

Features

🧸 Toy Image Fetcher (`fetch_toy_image`)

Downloads toy-related images from DuckDuckGo search
Automatically prefixes search terms with "toy" for better results
Supports downloading 1-10 images per request
Saves images to a specified directory

🖼️ Image Resizer (`resize_image`)

Resize images to specific dimensions
Option to maintain aspect ratio
High-quality resampling using Lanczos algorithm
Support for all common image formats

✂️ Background Remover (`remove_background_as_png`)

AI-powered background removal using state-of-the-art models
Multiple model options (u2net, u2netp, silueta, isnet-general-use)
Outputs PNG with transparent background
Preserves main object details

Related MCP server: MCP Image Tools Server

Prerequisites

Python 3.11 or higher
Docker (for containerized deployment)
Claude Code (for MCP client integration)

Installation

Option 1: Local Python Installation

Clone or create the project directory:

mkdir mcp-toy-image-tools && cd mcp-toy-image-tools

Install Python dependencies:
```
pip install -r requirements.txt
```
Run the server:
```
python server.py
```

Option 2: Docker Installation (Recommended)

Build the Docker image:

docker build -t mcp-toy-image-tools-server .

Create necessary directories:
```
mkdir -p images input output
```

Run the container:

docker run --rm -i \
  --name mcp-toy-image-tools \
  -v $(pwd)/images:/app/images \
  -v $(pwd)/input:/app/input \
  -v $(pwd)/output:/app/output \
  mcp-toy-image-tools-server

Claude Code Integration

Step 1: Configure Claude Code

Copy the MCP configuration to your Claude Code settings:

For Docker execution:

{
  "mcpServers": {
    "image-tools-server-docker": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--name", "mcp-toy-image-tools",
        "-v", "${PWD}/images:/app/images",
        "-v", "${PWD}/input:/app/input",
        "-v", "${PWD}/output:/app/output",
        "mcp-toy-image-tools-server"
      ],
      "cwd": "/path/to/your/mcp-toy-image-tools"
    }
  }
}

Update the cwd path to match your actual project directory.

Step 2: Restart Claude Code

After updating your MCP configuration, restart Claude Code to load the new server.

Usage Examples

Once integrated with Claude Code, you can use these commands:

Download Toy Images

Please use the fetch_toy_image tool to download 5 robot toy images to the ./images directory.

Resize Images

Can you resize the image at ./images/robot_toy_1.jpg to 800x600 pixels?

Remove Background

Please remove the background from ./images/robot_toy_1.jpg and save it as a PNG.

File Structure

mcp-toy-image-tools/
├── server.py              # Main MCP server implementation
├── requirements.txt       # Python dependencies
├── Dockerfile            # Docker container configuration
├── .mcp.json            # Claude Code MCP configuration
├── README.md            # This documentation
├── images/              # Directory for downloaded/processed images
├── input/               # Directory for input images (Docker)
└── output/              # Directory for output images (Docker)

Dependencies

Python Libraries

mcp: Anthropic's Model Context Protocol SDK
Pillow: Python Imaging Library for image processing
requests: HTTP client for downloading images
duckduckgo-search: DuckDuckGo search API client
torch/torchvision: PyTorch for AI model inference

System Dependencies (Docker only)

OpenGL libraries for image processing
GLib and threading libraries
Various image format support libraries

Configuration Options

Environment Variables

PYTHONPATH: Set to project directory for proper module resolution

Volume Mounts (Docker)

/app/images: Directory for downloaded and processed images
/app/input: Input directory for source images
/app/output: Output directory for processed images

Troubleshooting

Common Issues

"duckduckgo-search library not available" error:
```
pip install duckduckgo-search
```
Image download failures:
- Check internet connection
- Some images may be blocked by the source website
- The tool automatically retries with additional results
Background removal model download:
- First use may take longer as AI models are downloaded
- Ensure sufficient disk space (~100MB+ for models)
Permission errors (Docker):
- Ensure volume mount directories have proper permissions
- The container runs as non-root user mcp-user

Debug Mode

To run with debug logging:

# Direct Python
PYTHONPATH=. python server.py --log-level DEBUG

# Docker
docker run --rm -i -e LOG_LEVEL=DEBUG mcp-toy-image-tools-server

Claude Code Connection Issues

Server not appearing in Claude Code:
- Check that .mcp.json is in the correct location
- Verify the cwd path is correct
- Restart Claude Code after configuration changes
Tool execution errors:
- Check server logs for detailed error messages
- Ensure all dependencies are installed
- Verify file paths are accessible

Development

Adding New Tools

To add new image processing tools:

Define the tool in handle_list_tools():

Tool(
    name="your_new_tool",
    description="Description of what it does",
    inputSchema={...}
)

Implement the handler in handle_call_tool():

elif name == "your_new_tool":
    return await your_new_tool_function(arguments)

Add the async function implementation:

async def your_new_tool_function(arguments: dict[str, Any]) -> list[TextContent]:
    # Implementation here
    pass

Testing

Test the server independently:

echo '{"method": "tools/list", "params": {}}' | python server.py

License

This project is provided as-is for educational and development purposes. Please respect the terms of service of image sources and AI models used.

Contributing

Fork the repository
Create a feature branch
Make your changes
Test thoroughly
Submit a pull request

Support

For issues and questions:

Check the troubleshooting section above
Review Claude Code MCP documentation
Submit issues to the project repository

Note: This tool downloads images from the internet and uses AI models for processing. Please use responsibly and respect copyright and terms of service of source websites.

This server cannot be deployed

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

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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MCP Image Tools Server

Features

🧸 Toy Image Fetcher (fetch_toy_image)

🖼️ Image Resizer (resize_image)

✂️ Background Remover (remove_background_as_png)

Prerequisites

Installation

Option 1: Local Python Installation

Option 2: Docker Installation (Recommended)

Claude Code Integration

Step 1: Configure Claude Code

Step 2: Restart Claude Code

Usage Examples

Download Toy Images

Resize Images

Remove Background

File Structure

Dependencies

Python Libraries

System Dependencies (Docker only)

Configuration Options

Environment Variables

Volume Mounts (Docker)

Troubleshooting

Common Issues

Debug Mode

Claude Code Connection Issues

Development

Adding New Tools

Testing

License

Contributing

Support

Maintenance

Resources

Related MCP Connectors

Related MCP Servers