Stop building a web stack.
Start shipping your agent.
The web layer for your agent, already built. The crawlers, browsers, proxies, parsers and cache are running now. Send a URL, get clean text your model can read, with its source. Free while you build, paid when you grow.
- no crawlers to run
- no headless browsers
- no parsers to fix
- no cache to keep fresh
One call per page. Answers in milliseconds from the index, and up to 99.4% fewer input tokens than raw HTML on measured pages.
Three jobs
you probably recognise.
Lyrenth returns the page content. The answering, the researching and the embedding stay yours. Or start from something that already works: eleven ready-to-use agents, one command each, and the research one published on its own as lyrenth-research.
Everything on the left is ours.
On your side: one call.
Crawling, rendering, cleaning and caching all happen before you ask. Most pages you request have already been read, so yours comes back in milliseconds and the site is never touched again. The more people read through Lyrenth, the more of the web is already waiting when you arrive. When freshness matters, force_refresh re-indexes on demand.
One canonical AIDocument per URL. Written once, read by everyone: the work happens on our side, the call happens on yours.
We crawl the open web and render the pages that need a browser. It runs without you, around the clock.
One standing index in the middle: cleaned, normalized, held, and shared by every reader.
Your side is one request. Send a URL, get the document back in milliseconds. Done.
We crawl the open web and render the pages that need a browser. It runs without you, around the clock.
One canonical AIDocument per URL. Written once, read by everyone: the work happens on our side, the call happens on yours.
One standing index in the middle: cleaned, normalized, held, and shared by every reader.
Your side is one request. Send a URL, get the document back in milliseconds. Done.
What famous pages cost,
raw vs indexed.
Every row is a real page read through the index, with token economics reported by the API itself. Reproducible with one call.
The same shape,
for every URL.
Send any public URL, get one AIDocument back: the same grouped JSON envelope every time, versioned forever. Validate against the public JSON Schema.
Full AIDocument schema in the docs →How does AI
actually read you?
AI cannot recommend what it cannot read. Paste your URL and see exactly what an agent receives from your page: how much of it is real content, what is missing, and what to fix. Most sites have never been checked.
Try a page
your application needs to read.
No account for the first reads. Paste a URL, watch it resolve, and see what your model would receive: the same grouped JSON envelope every time, with the tokens it saved.
From Wikipedia, the free encyclopedia Methods for indexing the Internet **Web indexing**, or **Internet indexing**, comprises methods for indexing the contents of a [website](https://en.wikipedia.org/wiki/Website) or of the [Internet](https://en.wikipedia.org/wiki/Internet) as a whole. Individual websites or [intranet…
curl "https://api.lyrenth.com/v1/public/aidocument?url=https://en.wikipedia.org/wiki/Web_indexing"
claude mcp add --transport http lyrenth https://api.lyrenth.com/mcp \ --header "Authorization: Bearer $LYRENTH_API_KEY"
Ready to call it from your own code? The quickstart has the same request in nine languages, including Python, TypeScript and Go.
- 25 reads an hour with no account.
- 2,000 a month with a free key.
- The first 1,000 to claim it get Starter, 20,000 a month, free for 90 days.
- No card.
Point it at a URL and see.
Your first read takes about a minute. 2,000 a month free, no card, and nothing to install.