iflow-mcp_ia-programming-mcp-image 0.1.1

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MCP Server - Image

A Model Context Protocol (MCP) server that provides tools for fetching and processing images from URLs, local file paths, and numpy arrays. The server includes a tool called fetch_images that returns images as base64-encoded strings along with their MIME types.

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Table of Contents

• Features
• Prerequisites
• Installation
• Running the Server
  • Direct Method
  • Configure for Windsurf/Cursor
• Available Tools
  • Usage Examples
• Debugging
• Contributing
• License

Features

• Fetch images from URLs (http/https)
• Load images from local file paths
• Specialized handling for large local images
• Automatic image compression for large images (>1MB)
• Parallel processing of multiple images
• Proper MIME type mapping for different file extensions
• Comprehensive error handling and logging

Prerequisites

• Python 3.10+
• uv package manager (recommended)

Installation

1. Clone this repository
2. Create and activate a virtual environment using uv:

uv venv
# On Windows:
.venv\Scripts\activate
# On Unix/MacOS:
source .venv/bin/activate

3. Install dependencies using uv:

uv pip install -r requirements.txt

Running the Server

There are two ways to run the MCP server:

1. Direct Method

To start the MCP server directly:

uv run python mcp_image.py

2. Configure for Windsurf/Cursor

Windsurf

To add this MCP server to Windsurf:

1. Edit the configuration file at ~/.codeium/windsurf/mcp_config.json
2. Add the following configuration:

{
  "mcpServers": {
    "image": {
      "command": "uv",
        "args": ["--directory", "/path/to/mcp-image", "run", "mcp_image.py"]
    }
  }
}

Cursor

To add this MCP server to Cursor:

1. Open Cursor and go to Settings (Navbar → Cursor Settings)
2. Navigate to Features → MCP Servers
3. Click on + Add New MCP Server
4. Enter the following configuration:

{
  "mcpServers": {
    "image": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-image", "run", "mcp_image.py"]
    }
  }
}

Available Tools

The server provides the following tools:

fetch_images: Fetch and process images from URLs or local file paths Parameters: image_sources: List of URLs or file paths to images Returns: List of processed images with base64 encoding and MIME types

Usage Examples

You can now use commands like:

• "Fetch these images: [list of URLs or file paths]"
• "Load and process this local image: [file_path]"

Examples

# URL-only test
[
  "https://upload.wikimedia.org/wikipedia/commons/thumb/7/70/Chocolate_%28blue_background%29.jpg/400px-Chocolate_%28blue_background%29.jpg",
  "https://imgs.search.brave.com/Sz7BdlhBoOmU4wZjnUkvgestdwmzOzrfc3GsiMr27Ik/rs:fit:860:0:0:0/g:ce/aHR0cHM6Ly9pbWdj/ZG4uc3RhYmxlZGlm/ZnVzaW9ud2ViLmNv/bS8yMDI0LzEwLzE4/LzJmOTY3NTViLTM0/YmQtNDczNi1iNDRh/LWJlMTVmNGM5MDBm/My5qcGc",
  "https://shigacare.fukushi.shiga.jp/mumeixxx/img/main.png"
]

# Mixed URL and local file test
[
  "https://upload.wikimedia.org/wikipedia/commons/thumb/7/70/Chocolate_%28blue_background%29.jpg/400px-Chocolate_%28blue_background%29.jpg",
  "C:\\Users\\username\\Pictures\\image1.jpg",
  "https://imgs.search.brave.com/Sz7BdlhBoOmU4wZjnUkvgestdwmzOzrfc3GsiMr27Ik/rs:fit:860:0:0:0/g:ce/aHR0cHM6Ly9pbWdj/ZG4uc3RhYmxlZGlm/ZnVzaW9ud2ViLmNv/bS8yMDI0LzEwLzE4/LzJmOTY3NTViLTM0/YmQtNDczNi1iNDRh/LWJlMTVmNGM5MDBm/My5qcGc",
  "C:\\Users\\username\\Pictures\\image2.jpg"
]

Debugging

If you encounter any issues:

1. Check that all dependencies are installed correctly
2. Verify that the server is running and listening for connections
3. For local image loading issues, ensure the file paths are correct and accessible
4. For "Unsupported image type" errors, verify the content type handling
5. Look for any error messages in the server output

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.