Fetch with Images
Summary
This MCP server, developed by kazuph, enables web content fetching and image processing capabilities for AI assistants. It integrates with libraries like jsdom, Readability, and Sharp to extract readable content from web pages, convert HTML to Markdown, and process images for optimal viewing. The implementation handles robots.txt restrictions, merges multiple images vertically with size limits, and uses macOS clipboard operations for seamless image insertion. It's designed for scenarios requiring web scraping, content summarization, or image handling within AI conversations, allowing assistants to fetch and process web content on demand while respecting web standards and optimizing for readability.
Available Actions(6)
fetch_web_content
Fetch web content from a specified URL. Parameters: url (string, required), maxLength (integer, default: 20000), startIndex (integer, default: 0), raw (boolean, default: false), ignoreRobotsTxt (boolean, default: false)
fetch_article_title
Extract and display the title of the article from the fetched web content.
process_images
Process images from web pages with optional optimization. Enable with enableFetchImages (boolean, default: false), imageMaxCount (integer, default: 3), imageMaxHeight (integer, default: 4000), imageMaxWidth (integer, default: 1000), imageQuality (integer, default: 80)
paginate_images
Support pagination for images from a specified URL. Parameters: imageStartIndex (integer, default: 0), imageMaxCount (integer, default: 3)
optimize_jpeg
Automatically optimize images as JPEG for better performance.
extract_gif_frame
Extract the first frame from animated GIFs available in the fetched content.
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