Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized communication method designed to enhance the interaction between large language models (LLMs) and various applications. It facilitates a seamless exchange of contextual information, allowing LLMs to deliver more accurate and relevant responses. Historically, the challenge has been to provide LLMs with sufficient context to understand user intent fully. MCP addresses this by creating a structured way to send and receive data, making LLMs more adaptable and powerful.

The concept of context management in AI has evolved significantly. Early systems relied on simple keyword matching, which often led to misinterpretations. As LLMs became more sophisticated, the need for detailed contextual information grew. MCP emerged as a solution to this need, drawing on principles from API design and data serialization. It builds upon previous attempts to standardize LLM interactions, aiming to provide a more robust and scalable approach.