ScrapeGraphAI LLM-Powered Web Scraping with Graph Logic Pipelines
ScrapeGraphAI is a Python web scraping library that uses LLMs and directed graph logic to create intelligent scraping pipelines. Describe what data you want to extract in natural language and the library builds and executes the extraction pipeline automatically.
npx skills add agentskillexchange/skills --skill scrapegraphai-llm-web-scraping
ScrapeGraphAI takes a fundamentally different approach to web scraping by combining Large Language Models with directed graph computation. Instead of writing CSS selectors, XPath expressions, or regex patterns, you describe what information you want to extract in natural language and the library constructs a scraping pipeline that handles the extraction logic, navigation, and data structuring automatically.
What this skill actually does
How It Works
The library models scraping workflows as directed graphs where each node performs a specific operation: fetching pages, parsing content, extracting structured data via LLM, or transforming results. Built-in graph types include SmartScraperGraph for single-page extraction, SearchGraph for multi-page research, and SpeechGraph for audio content processing. The LLM component understands the page structure and extracts exactly the fields you request, returning clean structured data.
Key Capabilities
- Natural Language Extraction: Specify extraction targets in plain English. Ask for “all product names, prices, and ratings” and get structured JSON output without writing selectors.
- Multiple Source Support: Scrape websites, local HTML files, XML documents, JSON files, and Markdown content through the same interface.
- Multi-LLM Support: Works with OpenAI, Anthropic Claude, Google Gemini, Ollama local models, and other LLM providers. Run entirely locally with Ollama for privacy-sensitive tasks.
- Graph Pipeline Architecture: Compose custom scraping workflows by chaining graph nodes. Extend with custom nodes for specialized extraction logic.
- Built-in Browser Rendering: Uses Playwright under the hood for JavaScript-rendered pages. Handles SPAs and dynamic content automatically.
Integration Points
Install with pip install scrapegraphai followed by playwright install for browser support. The library integrates with LangChain, LlamaIndex, CrewAI, and Agno agent frameworks. SDK packages are available for both Python and Node.js. An MCP server is available for integration with AI coding assistants. Low-code integrations exist for Zapier, n8n, Pipedream, and Dify.
Agent Use Cases
Research agents can extract structured data from any webpage by describing the target fields in natural language, eliminating brittle selector-based extraction. Competitive intelligence agents can monitor product pages and extract pricing data across multiple sites. Content aggregation agents can pull article text, metadata, and media from diverse sources into a unified format. Market research agents can combine SearchGraph with analysis prompts to gather and summarize information across multiple search results in a single pipeline execution.