Scrapezy
Enables AI models to extract structured data from websites using the Model Context Protocol.
About
Scrapezy is a Model Context Protocol (MCP) server designed to work with AI models like those from Claude, allowing them to extract structured data from websites. It offers a streamlined way to fetch and process information based on specific prompts, making it an invaluable tool for automating data extraction tasks. The server is easily installable via Smithery or manually through npm, and integrates seamlessly with Claude Desktop by configuring the server within the application's configuration file. With Scrapezy, users can leverage the power of AI to gather data efficiently from web sources, simplifying workflows and enhancing productivity.
Key Features
- Extracts structured data from websites based on prompts.
- 1 GitHub stars
- Integrates with Claude Desktop for AI-powered data extraction.
- Provides API key authentication via environment variable or command-line argument.
- Offers both Smithery and manual installation options.
- Includes a debugging tool (MCP Inspector) to aid in troubleshooting.
Use Cases
- Extracting product information (name, price, description) from e-commerce sites.
- Gathering data for market research and competitive analysis.
- Populating databases with structured information from various websites.
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