---
title: "Fetch"
description: "Web content retrieval and HTML-to-markdown conversion for LLM consumption"
category: "mcp-servers"
tags: ["web", "utility", "server", "data", "real-time", "AI", "content conversion", "markdown"]
tech_stack: ["Web Scraping", "HTML Processing", "Markdown", "Content Extraction", "API Integration", "Large Language Models"]
---

Fetch acts as a Model Context Protocol server, letting AI assistants tap into and work with web content by turning HTML pages into clean markdown format. 

This change makes web content easier for large language models to digest. As a result, these models can analyze and reason about information from websites, documentation, and other online resources more effectively.

Developers can leverage Fetch to create AI applications that require real-time access to web data, content summarization, or information extraction from web pages. 

The markdown conversion keeps the essential structure intact while stripping away unnecessary HTML clutter, which enhances the context provided to LLMs. This leads to more accurate responses and better analysis.