
Image
โ 20from IA-Programming
Fetch and process images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings.
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.
Table of Contents
- Features
- Prerequisites
- Installation
- Running the Server
- Available Tools
- 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
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:
- Check that all dependencies are installed correctly
- Verify that the server is running and listening for connections
- For local image loading issues, ensure the file paths are correct and accessible
- For "Unsupported image type" errors, verify the content type handling
- Look for any error messages in the server output
uv venv
# On Windows:
.venv\Scripts\activate
# On Unix/MacOS:
source .venv/bin/activatePrerequisites
- Python 3.10+
- uv package manager (recommended)
Installation
- Clone this repository
- Create and activate a virtual environment using uv:
uv venv
# On Windows:
.venv\Scripts\activate
# On Unix/MacOS:
source .venv/bin/activate- Install dependencies using uv:
uv pip install -r requirements.txtRunning 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.py2. Configure for Windsurf/Cursor
Windsurf
To add this MCP server to Windsurf:
- Edit the configuration file at ~/.codeium/windsurf/mcp_config.json
- 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:
- Open Cursor and go to Settings (Navbar โ Cursor Settings)
- Navigate to Features โ MCP Servers
- Click on + Add New MCP Server
- Enter the following configuration:
{
"mcpServers": {
"image": {
"command": "uv",
"args": ["--directory", "/path/to/mcp-image", "run", "mcp_image.py"]
}
}
}No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.
Licensed under MITโ you can use, modify, and redistribute it under that license's terms.
License
This project is licensed under the MIT License - see the LICENSE file for details.