---
id: mcp-server-fetch
version: "2026.7.10"
license: MIT
license_treatment: permissive
maintenance: active
---

# mcp-server-fetch — A Model Context Protocol server providing tools to fetch and convert web content for usage by LLMs

License: permissive · Maintenance: active · Downloads: 1.1M/mo

## What it is and what it does

mcp-server-fetch is a Model Context Protocol server that bridges LLMs and the web by providing a standardized interface to fetch and process web pages. It retrieves HTML from URLs and converts it to markdown, making web content digestible for language models. The server exposes a fetch tool with parameters for URL, maximum content length, character-index-based pagination (via start_index), and raw-content mode, allowing models to read large pages in chunks.

The package is designed to integrate with LLM platforms like Claude.app and VS Code extensions that support MCP. It respects robots.txt by default (configurable), supports custom user-agents and proxy configuration, and includes safeguards against accessing local/internal IP addresses—though the documentation cautions that this remains a potential security risk. It depends on httpx and requests for HTTP operations, markdownify and readabilipy for content extraction, and pydantic for configuration validation.

Use it for:

- Enable Claude or other MCP-compatible LLMs to research topics by fetching and reading web pages during conversations
- Build automated workflows where an AI agent needs to gather information from multiple websites and synthesize it
- Integrate web-fetching capabilities into VS Code or other editors that support MCP servers for real-time web lookups
- Allow LLMs to verify claims or retrieve current information by fetching live web content
- Create chatbots or assistants that can answer questions by retrieving and processing relevant web pages on demand

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a Model Context Protocol server that fetches web pages and converts their HTML content to markdown, enabling LLMs to read and process web content through a standardized interface.

Yes. The package is actively maintained, has no known vulnerabilities, installs with low friction, and fills a clear need for LLM-to-web integration in the MCP ecosystem. The permissive MIT license removes legal friction. Install it if you are running an MCP-compatible LLM platform and need web-fetching capabilities; the security caution about internal IPs is a deployment concern, not a reason to avoid the package itself.

## Install

pip install mcp-server-fetch
uv add mcp-server-fetch
poetry add mcp-server-fetch

## Installing mcp-server-fetch

Before you install: Low friction install via pip or uvx. Active maintenance with recent release (35 days old) and strong repository signals (89561 stars). Requires Python 3.10 or later. Seven runtime dependencies are all established packages.

License in practice: MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart:

pip install mcp-server-fetch
python -m mcp_server_fetch

# Then configure in Claude.app or VS Code with:
# {"mcpServers": {"fetch": {"command": "python", "args": ["-m", "mcp_server_fetch"]}}}

# The server exposes a fetch tool that accepts url, max_length, start_index, and raw parameters.

Requires Python 3.10 or later. On Windows, may need PYTHONIOENCODING=utf-8 environment variable to avoid timeout issues. Optionally requires Node.js for a more robust HTML simplifier.

Verify before relying:

- Whether the server's HTML-to-markdown conversion handles complex layouts, tables, or interactive content reliably
- Performance characteristics when fetching large pages or many URLs in sequence
- How the server handles authentication-required pages or pages behind paywalls
- Specific rate-limiting or throttling behavior when used with multiple concurrent requests

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 1.1M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

mcp server web fetching, llm web content retrieval, html to markdown conversion, model context protocol fetch, web scraping for ai models, mcp web tools, llm internet access, mcp-server, llm-integration, web-scraping

[View on SkillFed](https://skillfed.io/packages/mcp-server-fetch) · [View on PyPI](https://pypi.org/project/mcp-server-fetch/)