Super Fetch MCP Server
The SuperFetch MCP server is a web content extraction tool based on the Model Context Protocol. It can intelligently crawl web pages, extract readable content using Mozilla Readability, and return it in an AI-friendly JSONL or Markdown format. It supports structured content blocks, built-in caching, and security protection.
rating : 2 points
downloads : 5.0K
What is SuperFetch MCP Server?
SuperFetch is a Model Context Protocol (MCP) server dedicated to intelligent web page content crawling and extraction. It is not just a simple web crawler. Instead, it uses Mozilla Readability technology to automatically identify and extract the main content of web pages, removing irrelevant elements such as advertisements, navigation bars, and footers, and then converts the content into a format that is easy for AI assistants to process. In simple terms, it allows AI to read web pages like humans, focusing only on truly valuable content rather than the cluttered information of the entire page.How to use SuperFetch?
Using SuperFetch is very simple and does not require installing any software. You just need to add the configuration in the AI assistant tool you are using (such as Claude Desktop, VS Code, Cursor, etc.). It supports one-click installation and can be used within a few seconds. There are two main ways to use it: 1. **JSONL format**: Obtain structured content blocks, suitable for AI analysis and processing. 2. **Markdown format**: Obtain a clean document format, suitable for human reading and document generation.Applicable scenarios
SuperFetch is particularly suitable for the following scenarios: • **AI assistants need to read web page content**: Enable AIs such as Claude and ChatGPT to access and understand web page information. • **Document generation and summarization**: Automatically extract the main content of articles to generate summaries or documents. • **RAG (Retrieval Augmented Generation) system**: Provide a high-quality web content source for the knowledge base. • **Content analysis and research**: Extract structured information from multiple web pages in batches for analysis. • **Technical document processing**: Extract technical content such as code examples and API documents.Main features
Intelligent content extraction
Use Mozilla Readability technology to automatically identify and extract the core content of web pages, intelligently removing irrelevant elements such as advertisements, navigation bars, and footers, and only retaining truly valuable information.
Multiple output formats
Supports two output formats: JSONL (structured data) and Markdown (document format), meeting the needs of different scenarios. JSONL is suitable for AI processing, and Markdown is suitable for human reading.
Structured content blocks
Decompose web page content into semantic blocks: headings, paragraphs, lists, code blocks, tables, images, quotes, etc., allowing AI to better understand and process the content structure.
Built-in cache system
Automatically cache the extracted content, reducing duplicate requests and improving response speed. The cache time and maximum number of cache entries can be configured to optimize performance.
Robust crawling mechanism
Supports retry mechanism, timeout control, and redirection handling to ensure successful content acquisition even in unstable network conditions.
Security-first design
Built-in security mechanisms such as SSRF protection, URL verification, and header cleaning to prevent malicious requests and attacks and ensure safe use.
Easy integration
Supports one-click installation and is compatible with all mainstream MCP clients (Claude Desktop, VS Code, Cursor, etc.) without complex configuration.
Advantages
Intelligent content extraction: Automatically identify and extract core content, removing irrelevant elements
AI-friendly format: Structured output optimized specifically for AI processing
Easy to use: One-click installation, no technical background required
Highly configurable: Supports multiple configuration options to adapt to different needs
Safe and reliable: Built-in multiple security protection mechanisms
Excellent performance: Cache and retry mechanisms ensure stable and efficient operation
Limitations
Dynamic content limitation: Limited support for content dynamically loaded by JavaScript
Login page limitation: Unable to access content on pages that require login
Anti-crawler websites: May be blocked by the anti-crawler mechanisms of some websites
Large file processing: Extra processing may be required for extremely large web page content
Format conversion: Format conversion of some complex web pages may not be perfect
How to use
Select your AI tool
Select the corresponding configuration method according to the AI assistant tool you are using. It supports mainstream tools such as Claude Desktop, VS Code, Cursor, Codex IDE, and Windsurf.
Add configuration
Add the SuperFetch configuration to the tool's configuration file. Most tools support one-click installation, and you just need to copy the configuration code.
Restart the tool
After saving the configuration file, restart your AI tool for the configuration to take effect.
Start using
Now you can use the SuperFetch tool in your AI assistant. You can request to extract web page content and choose the JSONL or Markdown format.
Usage examples
Technical blog content analysis
You are researching a certain technical topic and need to analyze multiple relevant blog articles. Using SuperFetch, you can quickly extract the core content of these articles, remove advertisements and navigation, and only retain the technical discussion part.
Product documentation conversion
You need to convert the online documentation of a certain product into a local Markdown file for offline reading or localization processing.
News summary generation
You need to quickly understand the headline news content of multiple news websites and generate a daily summary.
Academic paper collection
Researchers need to collect abstracts and key findings of academic papers in related fields.
Frequently Asked Questions
What is the difference between SuperFetch and ordinary web crawling?
Do I need programming knowledge to use it?
Which websites are supported?
Which format should I choose, JSONL or Markdown?
Is there a size limit for the extracted content?
How to ensure safe use?
Does it support Chinese websites?
What should I do if I encounter a website that cannot be accessed?
Related resources
Official GitHub repository
View source code, submit issues, and participate in contributions
MCP Protocol official website
Learn detailed information and specifications of the Model Context Protocol
NPM package page
View package versions, download statistics, and update logs
MCP Registry
Discover more MCP servers and tools
Problem feedback
Report bugs or propose feature suggestions

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