Why MCP does not work as well as marketing promises?

The article discusses the issues surrounding the Context Protocol Model and how it can lead to misunderstandings. In today's AI-driven world, where data is crucial for model performance, the author points out how a poor understanding of context results in inefficient outcomes. Deconstructing the protocol, the article provides examples that illustrate its weaknesses and suggests alternative approaches. Understanding these limitations is incredibly important for researchers and engineers looking to develop more advanced and successful AI models. Awareness of the protocol's flaws allows for better alignment of strategies and methodologies in AI development.