Stealthfetch FAQs

Question 1

Does Stealthfetch offer any security features for web scraping?

Accepted Answer

Yes, Stealthfetch prioritizes security with robust Server-Side Request Forgery (SSRF) protection. It performs double-validation of URLs – both before the request and after any redirects – to prevent malicious access to internal networks, a critical feature, especially when integrated as an MCP server.

Question 2

How does Stealthfetch handle anti-bot systems like Cloudflare or DataDome?

Accepted Answer

Stealthfetch intelligently detects anti-bot challenges and automatically escalates. It first attempts an efficient HTTP request with a Chrome TLS fingerprint. If blocked, it seamlessly switches to a stealth browser (Camoufox/Patchright) to bypass systems like Cloudflare, DataDome, and PerimeterX, ensuring successful content retrieval.

Question 3

Is Stealthfetch open-source or require an API key?

Accepted Answer

Stealthfetch is completely open-source, available under the AGPL-3.0 license, and requires no API key. This makes it a cost-effective and transparent solution for developers and organizations looking to integrate advanced web scraping capabilities into their projects.

Question 4

What is Stealthfetch and what is its main purpose?

Accepted Answer

Stealthfetch is a Python tool designed to convert any web page into clean, LLM-ready markdown. Its primary purpose is to simplify data extraction for AI applications by automatically bypassing common anti-bot systems and delivering a stripped-down, focused text output.

Question 5

What kind of content does Stealthfetch extract, and what does 'LLM-ready' mean?

Accepted Answer

Stealthfetch extracts clean, focused markdown by intelligently stripping away navigation menus, advertisements, and other boilerplate content. 'LLM-ready' means the output is optimized for language models, providing only the essential text needed for training, fine-tuning, or RAG applications, free from distracting elements.

Stealthfetch

Stealthfetch

Key Features

Use Cases

Key Features

Use Cases