Scrapecraft is an AI-driven web scraping editor that allows users to effortlessly build, test, and deploy web scrapers using natural language. With its visual workflow builder, it simplifies data extraction tasks for various applications.
claude install ScrapeGraphAI/scrapecrafthttps://github.com/ScrapeGraphAI/scrapecraft
["1. Open Scrapecraft and click 'New Scraper'. Select 'Web Scraper' as your project type.","2. In the natural language input box, describe your scraping task using the prompt template. Be specific about the data you need and any challenges the website presents.","3. Review the generated scraper workflow. Use the visual editor to adjust selectors, add steps, or modify outputs as needed.","4. Test your scraper on a small scale first. Use the 'Test' button to run it against a sample page and verify the output.","5. Once satisfied, deploy your scraper. Set your preferred schedule and output destination. For better results, connect your Rive account for real-time collaboration and monitoring."]
Extracting detailed product information from multiple e-commerce platforms to analyze pricing trends.
Gathering competitive intelligence by scraping data from competitor websites for market analysis.
Automating the collection of data for market research surveys by scraping relevant online sources.
Building custom scrapers to monitor changes in website content for alerts on price drops or new product launches.
claude install ScrapeGraphAI/scrapecraftgit clone https://github.com/ScrapeGraphAI/scrapecraftCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a web scraper to extract [DATA_TYPE] from [WEBSITE_URL]. The scraper should handle [SPECIFIC_CHALLENGES] such as dynamic content loading or CAPTCHAs. Output the data in [DESIRED_FORMAT] and save it to [DESTINATION].
Scraper successfully created. Here's a summary of the configuration: 1. Target Website: https://www.example-retailer.com 2. Data Type: Product prices and availability 3. Challenges Handled: Dynamic content loading via JavaScript rendering 4. Output Format: CSV with columns for product name, price, availability status, and last updated timestamp 5. Destination: Google Drive folder 'Retail Price Tracking' The scraper will run daily at 8 AM and 6 PM, with error notifications sent to your email. You can monitor progress and results in the Rive dashboard.
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