ScrapeGraphAI
Turn any webpage into markdown, structured JSON, or scheduled change alerts through a single credit-based scraping API, rebuilt on a faster V2 architecture in April 2026.
The verdict on ScrapeGraphAI: Developers tired of maintaining CSS selectors that break every time a website redesigns ScrapeGraphAI's real value is resilience: because you describe what you want in natural language and the model identifies it regardless of HTML structure, it survives the site redesigns that break selector-based scrapers on a recurring basis. Pricing: Free (500 credits) / $17/mo Starter / $85/mo Growth. Last reviewed: August 2026.
Best For
Developers tired of maintaining CSS selectors that break every time a website redesigns
Standout Feature
Describe what you want in natural language and the LLM extracts it regardless of the page's HTML structure
TL;DR
Genuinely more resilient to layout changes than traditional scrapers, per-page LLM costs and accuracy vary by site.
Alternatives
Overview
ScrapeGraphAI is a web scraping library and API that uses large language models to extract structured data from web pages, instead of writing CSS selectors or XPath rules that break when a website redesigns, you describe what you want in natural language and the LLM identifies and extracts it from whatever HTML structure the page has. This prompt-based approach makes scrapers significantly more resilient to site changes and removes the need for CSS/XPath expertise. ScrapeGraphAI supports multiple scraping modes: SmartScraperGraph (single-URL extraction from a prompt), SearchGraph (searches the web and extracts structured data from multiple results), SpeechGraph (converts scraped content to audio), and OmniScraperGraph (handles PDFs and other file types).
The library runs against multiple LLM backends, OpenAI, Anthropic, Groq, Ollama, and others, giving teams flexibility to use a local model for cost-sensitive high-volume scraping. Output is structured data (JSON, CSV, or custom schema) rather than raw text, making it production-ready for data pipelines without post-processing. Available as an open-source Python library and as a hosted API for teams that don't want to manage their own LLM infrastructure.
Most suitable for market intelligence, price monitoring, lead data collection, and any extraction task where the target site changes structure too frequently for traditional selector-based scrapers to maintain reliably.
Our Take
That's a meaningful operational advantage if you're maintaining scrapers against sites that change. The tradeoffs are per-page LLM costs and accuracy that varies by site complexity. This earns its keep for developers who are tired of maintaining brittle CSS selectors and would rather pay a small cost-per-page than absorb recurring maintenance work after every layout change.
Key Features
- Prompt-based extraction
- Structured output (JSON)
- Library and hosted API
- Handles dynamic sites
- • No selectors to maintain
- • Flexible extraction
- • Good for changing layouts
- • LLM costs per page
- • Accuracy varies by site
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