URL to Markdown Converter
Any web page as clean, LLM-ready Markdown
What Is the URL to Markdown Converter?
The URL to Markdown Converter loads any web page in a real browser and turns it into clean Markdown, with headings, lists, links and tables intact. Choose main content only to drop the navigation, footers and sidebars. The result is ready to paste into an LLM prompt, a RAG pipeline or your notes, with a word count and token estimate attached.
Key Features
Why LLMs Prefer Markdown
Raw HTML is mostly markup: scripts, class names and layout wrappers that waste tokens and distract a model. Markdown keeps the structure that carries meaning, like headings, lists and links, and drops the rest. A typical page shrinks to a fraction of its HTML size, which means cheaper prompts and better answers.
Scraping Pages That Fight Back
Plenty of modern sites render content with JavaScript, and many block simple scrapers outright. This converter loads pages in a full browser through rotating proxies, which gets past most of that. If you're converting pages at scale yourself, you'll need the same two ingredients: a headless browser and a proxy pool that doesn't get flagged.
Common Use Cases
- Feeding web pages to ChatGPT or Claude without the clutter
- Building a document set for a RAG pipeline
- Saving articles as clean notes in Obsidian or Notion
- Converting documentation pages for an internal knowledge base
Frequently Asked Questions
Is the URL to Markdown Converter free?
Yes. It's free with a ProxyHorizon account, and every account gets 25 runs a day shared across all our data tools. You can read about the tool without signing in, but running it needs an account because each run fetches live data.
Does it work on JavaScript sites?
Yes. Pages are rendered in a real browser before conversion, so content loaded by JavaScript is included.
What does “main content only” do?
It removes menus, headers, footers, sidebars and cookie banners, leaving the article or main body. Choose full page if you need everything.
Is there a size limit?
The first 100,000 characters are shown, which covers almost any article. For bigger pages, convert sections separately.
How are tokens estimated?
At roughly one token per four characters of English text, a common rule of thumb. Exact counts depend on the model's tokenizer.
Scraping sites like this every day?
Proxies for web scraping