Web data API that turns pages into Markdown or JSON for AI models, with search, crawl and natural-language page interaction.

ScrapeGraphAI overview and key facts (October 2026)
Open-source Python library that builds scraping pipelines with LLMs: describe the data you want and it extracts it from pages or files.
What is ScrapeGraphAI?
ScrapeGraphAI is an open-source Python library that uses language models and graph-based pipelines to extract data from websites and local documents. You state what you need in plain language.
The library offers ready-made pipelines, called graphs, for common scraping jobs. The most used one, SmartScraperGraph, takes a prompt and a source URL and returns the requested data. It runs on Python, uses Playwright to fetch pages and works with the language model of your choice. The team behind it also sells a hosted API with Python and Node SDKs and connectors for Zapier, n8n, Bubble and Dify. The repository is published under the MIT license.
ScrapeGraphAI AI features and use cases
- Extracts data from a promptYou describe the fields you want, such as company name, contact page and product list, and the language model reads them from the page. Analysts can collect data from sites with changing layouts without writing selectors.
- Reads local documentsThe same pipelines work on XML, HTML, JSON and Markdown files. Teams can pull structured fields out of exported pages or documentation that already sits on their own drives. No web request is needed in this case, which keeps the data on your own systems when a local model is used.
- Plugs into agent frameworksIntegrations for LangChain, LlamaIndex and CrewAI and an MCP server let agents call the scraper as a tool. An agent can then collect data from a page as one step of a larger task.
What sets ScrapeGraphAI apart
- Model-agnostic: works with the language model you connect, including locally hosted models.
- README and documentation available in eleven languages, including German.
Where ScrapeGraphAI is strongest
ScrapeGraphAI is an open-source Python library installed from PyPI and used worldwide; documentation exists in eleven languages including German.
Questions to ask before you buy ScrapeGraphAI
Each extraction calls a language model, so costs and data flows depend on the model provider you choose; with a cloud model, page content leaves your systems. LLM extraction can return wrong or missing fields, so validate samples before relying on the output. Self-hosting means your team maintains the library and Playwright. The separately sold managed API offers features for bypassing bot protection, with stealth rendering and anti-bot handling included. Using them can breach the target sites' terms of use and is legally risky in Germany, for example under Section 202a of the German Criminal Code (StGB) or database rights. Have their use legally reviewed before deployment.
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Questions about ScrapeGraphAI
Is ScrapeGraphAI free?
The library is free under the MIT license. You pay for the language model you connect, or for the separate hosted API if you use it.
Which languages can we write prompts in?
Prompts go to the language model you choose, so any language the model handles works. The project documentation itself is available in eleven languages, including German.
Is the repository maintained?
Yes. On September 28, 2026 it had 31,378 stars and the last push was on September 25, 2026.
ScrapeGraphAI update historyno updates yet
No changes recorded for ScrapeGraphAI yet.
Changes the vendor made and confirmed user reports, each checked against the vendor's own pages. We review every tool monthly.
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