LLM-Ready Web Scraper – RAG & Vertical Data Extraction
Under maintenancePricing
from $5.00 / 1,000 url crawleds
LLM-Ready Web Scraper – RAG & Vertical Data Extraction
Under maintenanceScrapes any URL and returns clean LLM-ready content. Strips ads, nav, and boilerplate. Returns markdown, chunked text, token estimates, and metadata. Vertical modes for Legal, Medical, Property, E-commerce, Research, and News. Firecrawl alternative at $0.005 per URL.
Pricing
from $5.00 / 1,000 url crawleds
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joseph fadero
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15 hours ago
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LLM-Ready Web Scraper – RAG Data Extraction with Vertical Processing
The affordable Firecrawl alternative. $0.005 per URL. No subscription.
Scrapes any public URL and returns clean, structured content optimised for LLMs and RAG pipelines — stripped of navigation, ads, cookie banners, and HTML boilerplate.
What makes it different
- Vertical processing modes — Legal, Medical, Property, E-commerce, Research, and News modes apply domain-specific extraction rules for better content quality
- RAG-ready chunking — splits content into configurable token-sized chunks ready for embedding
- Token estimation — every result includes estimated token count so you know your LLM context usage upfront
- Pay per URL — $0.005/URL, no subscription
Use cases
- Feed RAG pipelines with fresh web content for Claude, GPT-4, or LlamaIndex
- Build AI agents that need live web data
- n8n/Make: scrape URLs from a spreadsheet → get clean markdown → send to your LLM
- Research aggregation: scrape multiple sources → chunk → embed → search
- Legal research: extract clean text from case law and statutes
- Property analysis: extract listing descriptions for AI comparison
Pricing
| Event | Price |
|---|---|
| Run started | $0.05 |
| URL crawled (no chunks) | $0.005 |
| URL crawled (with chunking) | $0.008 |
| URL failed | $0.001 |
100 URLs = $0.55 total. Firecrawl Hobby plan: $19/month for 500 URLs.
Input
| Field | Default | Description |
|---|---|---|
| urls | required | Array of URLs to scrape |
| outputFormat | markdown | markdown / plaintext / json |
| vertical | general | general / legal / medical / property / ecommerce / research / news |
| chunkContent | false | Split into RAG-sized chunks |
| chunkTokenSize | 512 | Target tokens per chunk (128–4096) |
| includeMetadata | true | Include title, author, dates, word/token count |
| removeElements | [] | Extra CSS selectors to strip |
| followLinks | false | Follow internal links from starting URLs |
| maxDepth | 1 | Link follow depth (1–3) |
| maxPagesPerUrl | 10 | Max pages per starting URL |
Output fields
url,sourceUrl,crawledAttitle,description,author,publishDate,languagewordCount,estimatedTokenscontent— clean text in chosen formatvertical— which extraction mode was appliedchunks— array of{ index, content, tokenEstimate }when chunking enabledstatus— success / failed / partialchargedEvent
Example n8n workflow
Apify node → this actor → Claude AI node → Google Sheets
