A sales team asks an AI agent to summarize a customer account, check the calendar, and prepare a follow-up. Each step touches a different business system. Without a shared way for applications to describe available data and actions, every connection can become a separate integration project with its own setup and maintenance.<\/p>\r\n\r\n\r\n\r\n
The Model Context Protocol (MCP)<\/strong> is an open standard for connecting AI applications to external systems. It gives compatible clients and servers a common way to exchange requests and results. In practical terms, an MCP server can make selected tools, information, or prompt templates available to an AI application.<\/p>\r\n\r\n\r\n\r\n MCP can make integrations more consistent. It does not automatically make systems compatible, authorize every action, or guarantee that an agent will use a tool correctly. A business still needs to choose what the agent can access, what it may change, and where a person must approve the next step.<\/p>\r\n\r\n\r\n\r\n Plain definition:<\/strong> MCP is a shared protocol that lets an AI application discover and interact with capabilities exposed by an MCP server, such as retrieving information or calling a defined tool.<\/p>\r\n<\/blockquote>\r\n\r\n\r\n\r\n This guide explains the protocol without assuming you write software. It focuses on where MCP fits in a business agent, the questions to ask a platform vendor, and the controls to plan before connecting it to real systems.<\/p>\r\n\r\n\r\n\r\n\r\n