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
Fetches web content from a specified URL. Parameters: url (string, required), maxLength (number, default: 20000), startIndex (number, default: 0), raw (boolean, default: false), enableFetchImages (boolean, default: false)
fetch_article_title
Extracts and displays the title of the article from the fetched web content.
process_images
Processes images from the fetched web content with options for optimization. Parameters: imageMaxCount (number, default: 3), imageMaxHeight (number, default: 4000), imageMaxWidth (number, default: 1000), imageQuality (number, default: 80), enableFetchImages (boolean, default: false)
paginate_content
Supports pagination for both text and images in the fetched content. Parameters: imageStartIndex (number, default: 0)
optimize_jpeg
Automatically optimizes images as JPEG for better performance.
extract_gif_frame
Extracts the first frame from animated GIFs found in the fetched web content.
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