What the "C" in MCP actually means

In episode two of the Fast MCP podcast, the concept of "context" in the realm of AI and its varied implications across different layers such as model, server, and application are dissected. Jeremiah Lowin, CEO, and Radhika Gulati, Product Marketing, delve into the complexities of context, explaining how it influences the behavior and decision-making of AI models by detailing the information available to them. The discussion highlights the challenges of managing context windows, which can overflow, leading to inefficiencies, and the evolution of context engineering as a practice to optimize the minimal yet effective delivery of context. The episode also addresses the confusion around the term "context" due to its multiple meanings in FastMCP, emphasizing the distinction between model context and server context. Additionally, the conversation touches on the development of MCP servers, the importance of progressive disclosure over the handshake problem, and how recent advancements such as tool search and code mode have made MCP servers more efficient. Finally, the podcast notes the upcoming changes with the MCP SDK version 2 and its implications for users, urging them to prepare for potential breaking changes and consider transitioning to FastMCP 4.

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