Your AI feature is only as good as what you feed it.
And what you have to feed it is a docs site that renders in JavaScript, 400 scanned PDFs, and a help centre nobody has exported since 2023.
So you write a scraper. Then a PDF parser. Then OCR. Then you're picking a chunking strategy, an embedding model, a vector store. Three weeks gone and the feature still isn't built.
That's the part we deleted. 👇
curl -X POST https://crawl.sarv.com/api/kb/$KB_ID/jobs \
-H "x-api-key: $SARVCRAWL_KEY" \
-d '{"type":"crawl","url":"https://docs.yoursite.com"}'
One call in. Clean markdown out — indexed, chunked, embedded, searchable by keyword and by meaning. No pipeline. No vector database to run.
🚀 Try it free → crawl.sarv.com
1 billion tokens on sign-up. No card.
🧰 What it does
| 🕷️ | Crawl a whole site — JS-rendered pages included | docs → |
| 📄 | Scrape one page to clean markdown | docs → |
| 🗺️ | Map every URL before you commit to a crawl | docs → |
| 📎 | Upload PDF, DOCX, XLSX, PPTX, CSV, images — OCR included | docs → |
| 🔄 | Monitor a source and re-crawl only what changed | docs → |
| 🔍 | Search by keyword, or by meaning | docs → |
🔌 Where it plugs in
| 🤖 | MCP — crawl and search from Claude Code, Cursor, VS Code | docs → |
| 🟢 | Node SDK | docs → |
| 🐍 | Python SDK | docs → |
| ⌨️ | CLI | docs → |
| 🔗 | n8n nodes | docs → |
🔎 Every answer traces back to a page you can open
The console isn't a wrapper on the API. It's where you check the crawl, read the exact chunks your model will be handed, and find the bad conversion before your users do.
Most tools give you a vector and a shrug. This one gives you a score for the conversion and a link to the source page.
🏠 Or self-host it
Open source, Apache-2.0, one .env and one docker compose up -d. Cloud when you want it to be someone else's problem, self-hosted when it can't leave your network — same API either way.
🚀 crawl.sarv.com — 1 billion tokens free
What are you trying to make searchable? Tell me in the comments — I'm curious which sources break it. 👇
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