AnyCrawler Free Crawl
Public URL to JSON and Markdown
What it does
AnyCrawler Free Crawl takes one public URL and returns JSON with Markdown and page metadata, without an account or API key.
Try a free web crawler in your browser: enter one public URL and receive clean Markdown, page details, and crawl metadata as JSON with no API key.
Paste a web page URL to retrieve its readable content, title, description, HTTP status, and crawl metadata as JSON. No account or API key is required for this quick test. Enter a complete http or https URL that is reachable without signing in. The free web crawler turns a public page into a compact JSON response. The main content is normalized as Markdown so it is easier to inspect, store, summarize, or pass to an AI model than the original HTML document. Source and status fields stay alongside the extracted content, which makes a quick test useful for both content review and early integration work. A single live crawl can answer practical questions about page access, extracted text, and…from anycrawler.com
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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