Image Process MCP Server

Overview

The Image Process MCP Server is a lightweight, Node‑based service that exposes common image manipulation capabilities to AI assistants via the Model Context Protocol. By leveraging the highly optimized Sharp library, it offers developers a fast and reliable way to resize, crop, rotate, convert formats, or inspect images directly from within a conversational agent. This eliminates the need for external image‑processing pipelines and keeps image workflows self‑contained within the MCP ecosystem.

The server solves a frequent pain point for developers building AI‑powered applications: integrating image manipulation without writing custom code or invoking bulky command‑line tools. Whether an assistant is generating thumbnails for a gallery, reformatting user uploads for web delivery, or extracting metadata for analytics, the MCP server delivers a consistent API that can be called from any Claude prompt. The service is platform‑agnostic, with simple configuration for macOS/Linux and Windows, making it straightforward to deploy in CI/CD pipelines or local development environments.

Key features are presented as discrete tools:

• Resize Image – Adjusts width and height with flexible fitting options (cover, contain, fill, etc.).
• Convert Format – Transforms images between JPEG, PNG, WebP, AVIF, TIFF, and GIF while controlling compression quality.
• Crop Image – Extracts a rectangular region by specifying pixel offsets and dimensions.
• Rotate Image – Rotates an image by any degree value, useful for correcting orientation or creating artistic effects.
• Get Image Info – Returns metadata such as dimensions, format, and color depth for inspection or validation.

These tools are exposed through the MCP interface, so an AI assistant can invoke them by simply describing the desired transformation. For example, a user might ask Claude to “resize an image to 500 pixels wide,” and the assistant will translate that request into a call with the appropriate parameters. The server then processes the image and returns the path to the newly created file, allowing the assistant to continue with further tasks or present the result directly to the user.

In real‑world scenarios, this MCP server shines in content management systems, e‑commerce platforms, and social media applications where image assets must be transformed on demand. It also benefits chatbot services that offer photo editing features without exposing the underlying complexity to end users. By integrating seamlessly with existing AI workflows, developers can focus on higher‑level logic while delegating low‑level image operations to a proven, performance‑optimized backend.