The Model Context Protocol (MCP) is an open, standardized protocol designed to enable structured interactions between AI models and external tools, data sources, and memory systems. It addresses the limitations of static model prompts by providing a turn-based, schema-bound communication layer that allows for dynamic, tool-augmented workflows in language models. MCP enables models to interact with external tools through OpenAPI specifications, maintaining security, interoperability, and consistency across ecosystems. The protocol's architecture includes a modular structure separating the responsibilities of the model, tools, and runtime, ensuring flexibility, composability, and control over tool execution. Despite its potential, MCP faces challenges such as limited model support, runtime complexity, tool spec overhead, latency from multi-step turns, debugging requirements, and an early ecosystem stage, which need to be addressed for widespread adoption.