{"id":720132,"date":"2025-08-21T09:58:58","date_gmt":"2025-08-21T07:58:58","guid":{"rendered":"https:\/\/www.devoteam.com\/expert-view\/model-context-protocol-mcp-explained\/"},"modified":"2025-10-30T16:39:01","modified_gmt":"2025-10-30T15:39:01","slug":"model-context-protocol-mcp-explained","status":"publish","type":"expert-view","link":"https:\/\/devoteam.info\/ch\/expert-view\/model-context-protocol-mcp-explained\/","title":{"rendered":"Model Context Protocol (MCP) Explained"},"content":{"rendered":"\n
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Written as part of our AI Upskilling Program<\/strong><\/h2>\n\n\n\n

This article was created as part of the Global Devoteam AI Upskilling Program<\/a>, where employees share their knowledge to accelerate their learning. The program’s key objective is to provide a foundation in AI for every employee and apply these new skills in our work. Do you want to work with us? Check out our career opportunities.<\/p>\n\n\n\n

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Career Opportunities<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

As AI advances from conversational chatbots to more autonomous agents, a standardised framework is essential to govern how these systems interact with external tools and data. Acting as a ‘virtual operating system’ for AI, Model Context Protocol (MCP) gives models a clear map of available tools and the rules for using them. It transforms passive models that only talk into capable agents that can perform real-world tasks. For businesses, this protocol provides the essential control, safety, and scalability to deploy intelligent systems that don’t just answer questions, but get things done.<\/p>\n\n\n\n

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What you’ll read in this article:<\/h3>