The text explores the evolution of web scraping, contrasting traditional methods with the AI-driven Model Context Protocol (MCP). Traditional web scraping, which requires coding knowledge and is sensitive to changes in web layouts, involves a four-step process of sending HTTP requests, parsing HTML, extracting data using CSS selectors or XPath, and handling dynamic content with browser automation tools like Selenium or Playwright. In contrast, the newly introduced MCP, released by Anthropic, simplifies the process by allowing users to provide plain-English instructions to AI, which then selects the appropriate tool for data extraction. MCP promises lower maintenance as it adapts to minor layout changes, although it may incur higher costs per request. This approach is particularly suited for rapid prototyping or sites that frequently change, while traditional methods remain optimal for high-volume, stable sites where control and efficiency are prioritized. The text suggests a hybrid future, advocating for the use of MCP for quick prototyping and traditional methods for stable operations, with platforms like Bright Data offering infrastructure to support both approaches.