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Using Cloudinary's New MCP Server to Scrape Mozarella, Camembert and Parmesan
- The article discusses using Cloudinary's MCP server to scrape images of various types of cheese like Mozarella, Camembert, and Parmesan for a machine learning model.
- Custom ML models require training with good-quality images, and Cloudinary's MCP server provides a solution for web scraping images.
- The Model Context Protocol (MCP) enables AI agents like Cheesy MCP to gather images and automate asset management.
- The author leverages the MCP tool to curate cheese images, demonstrating the functionality within Cursor, an IDE.
- Cloudinary offers various MCP servers for asset management, environment configuration, structured metadata, content analysis, and workflow automations.
- Users can install MCP servers easily using Cursor deeplinks and update credentials for Cloudinary account integration.
- The process involves scraping images, curating, and uploading with the assistance of the AI-powered agent and interacting via chat.
- Upon approval, the system uploads tagged images to the user's Cloudinary account for easy management.
- The integration of IDEs like Cursor with MCP servers allows for seamless automation and control over image processing workflows.
- The article encourages readers to explore the capabilities of Cloudinary's MCP servers and share their projects utilizing the technology.
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