Fetch MCP Server 1kd
F

Fetch MCP Server 1kd

An MCP server that provides web content crawling functionality, can convert HTML to Markdown for processing, and supports chunked reading of content.
2.5 points
5.9K

What is the Fetch MCP Server?

This is a web content acquisition service specifically designed for large language models (LLMs). It can automatically access specified web URLs, convert complex HTML web pages into concise Markdown format, and help AIs understand and process online content more efficiently.

How to use the Fetch MCP Server?

Simply specify the target URL through a simple API call, and the server will automatically complete content crawling and format conversion. You can also control the length and starting position of the returned content.

Use cases

Suitable for AI application scenarios that require real-time access to online information, such as news summary generation, web content analysis, knowledge base updates, etc.

Main features

Intelligent content crawling
Automatically identify the main content of the web page and filter out advertisements and irrelevant elements
HTML to Markdown conversion
Convert complex HTML to concise and readable Markdown format
Chunked reading
Support segmented retrieval of long document content through the start_index parameter
Advantages
Simplify the complexity of AI processing web content
Support chunked reading of large documents to avoid memory overflow
Provide two format options: original HTML and converted Markdown
Limitations
Unable to handle web pages that require login
Content rendered by JavaScript may not be fully retrieved
There is a limit on the length of the default returned content (5000 characters)

How to use

Install the service
Choose to install the server components via uv or pip
Call the fetch interface
Send a request containing the target URL to the service
Process the returned result
Retrieve the converted Markdown content or the original HTML

Usage examples

News summary generation
Crawl the latest articles from news websites and generate summaries
Technical document analysis
Read long technical documents in chunks for analysis

Frequently Asked Questions

Why is the content of some web pages not fully retrieved?
How to improve the content retrieval speed?
What is the difference between the uv and pip installation methods?

Related resources

uv official documentation
Usage guide for the uv installation tool
Markdown syntax reference
Standard reference for Markdown format
HTML parsing examples
Code repository for usage examples

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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