Provides Model Context Protocol tools for fetching, processing, and base64-encoding images from URLs, local files, and numpy arrays with automatic compression, MIME type handling, and parallel processing.
Unlock the full potential of MCP Image Server through LangDB's AI Gateway. Get enterprise-grade security, analytics, and seamless integration with zero configuration.
Free tier available • No credit card required
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.
If you find this project helpful and would like to support future projects, consider buying us a coffee! Your support helps us continue building innovative AI solutions.
Your contributions go a long way in fueling our passion for creating intelligent and user-friendly applications.
uv venv # On Windows: .venv\Scripts\activate # On Unix/MacOS: source .venv/bin/activate
uv pip install -r requirements.txt
There are two ways to run the MCP server:
To start the MCP server directly:
uv run python mcp_image.py
To add this MCP server to Windsurf:
{ "mcpServers": { "image": { "command": "uv", "args": ["--directory", "/path/to/mcp-image", "run", "mcp_image.py"] } } }
To add this MCP server to Cursor:
{ "mcpServers": { "image": { "command": "uv", "args": ["--directory", "/path/to/mcp-image", "run", "mcp_image.py"] } } }
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
You can now use commands like:
# 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"
]
If you encounter any issues:
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
Discover shared experiences
Shared threads will appear here, showcasing real-world applications and insights from the community. Check back soon for updates!