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.
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
Fit Score: use-case reference
How this is scoredScrapeGraphAI scored 1 to 5 on five dimensions for the named use cases below. Part of our catalog-wide use-case reference, not a product-quality review rating.
Developer maintaining scrapers against websites that redesign frequently
4.2/5- Capability
- 5/5
- Reliability
- 4/5
- Value
- 4/5
- Ease
- 4/5
- Compatibility
- 4/5
Because extraction is described in natural language rather than tied to CSS selectors, it survives site redesigns that break selector-based scrapers, which is the tool's core operational advantage for developers tired of recurring scraper maintenance.
High-volume scraping where per-page cost must stay minimal
3.0/5- Capability
- 3/5
- Reliability
- 3/5
- Value
- 2/5
- Ease
- 4/5
- Compatibility
- 3/5
Cons flag LLM costs per page and accuracy that varies by site complexity, so at high volume the per-page model cost becomes the deciding factor rather than the selector-resilience advantage.
Editorial judgment grounded in this tool's own published pricing, features, and our existing pros and cons, not a certification or a measured benchmark. Product quality is assessed separately under our review methodology.
Overview
Not yet reviewedProduct quality is assessed from original evidence. How reviews work.
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.
The source of the legacy catalog rating and review count has not been substantiated. Neither is presented here as a verified review rating or included in review structured data.
Workflow Fit Scores are separate, use-case-specific editorial judgments, not user-review averages. Read the Fit Score methodology.
- • No selectors to maintain
- • Flexible extraction
- • Good for changing layouts
- • LLM costs per page
- • Accuracy varies by site
Key Features
- Prompt-based extraction
- Structured output (JSON)
- Library and hosted API
- Handles dynamic sites
Trust & Data
Verified 2026-09
- Training on your data
- Opt-out availableScrapeGraphAI's terms draw a tiered line: data generated on the Free plan or trial may be used for model training, evaluation, and other research or improvement purposes as a condition of free access, with the practical opt-out being to stop using the free tier, while data from paid Team or Enterprise usage is explicitly not used for training unless the customer separately opts in. The open-source library only collects anonymous, opt-in telemetry.
- Compliance
- Not published
- Retention
- Retained only as long as necessary for the stated purposes or legal obligations; no specific day or month figure is published.
- Export
- Not published
Sources: scrapegraphai.com/terms, scrapegraphai.com/privacy
As published by the vendor. Verify independently before purchase decisions.
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.