Model Context Protocol Explained: How MCP Bridges AI Agents and External APIs

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Model Context Protocol (MCP) is a structured framework that enables AI assistants like Claude, Codex, or Kiro to interact with external systems such as REST APIs and databases. Instead of exposing raw API endpoints directly to an AI, an MCP server acts as a translation layer, converting simple AI-friendly tool calls into the complex HTTP requests an underlying API requires. For example, a tool like create_todo accepts plain parameters such as title and priority, while the MCP server internally maps these to the specific fields and IDs the target API expects. Developers configure AI clients to connect to an MCP server via a JSON file that specifies the server name, communication type, startup command, and required environment variables. This abstraction keeps internal implementation details hidden from the AI while giving it a cleaner, more reliable interface to work with.

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