Understanding MCP Architecture: LLM + API vs Model Context Protocol As AI and machine learning (ML) continue to transform industries and applications, developers face a critical question: how to design and implement scalable, efficient, and user-friendly systems that integrate language models. In this article, we'll explore the differences between two architectural approaches: using a Language Model as a Service (LLM + API) and implementing the Model Context Protocol (MCP). We'll walk through a real-world example of a chatbot that works with PDFs, highlighting what MCP brings to the table. The Goal User asks in natural language → chatbot reads/searches PDFs → returns an answer. This simple interaction hides complex technical challenges: text extraction, search across documents, summarization of sections, and more. We'll examine two ways to achieve this goal: LLM + API : Directly call a language model's API, wire tools together manually, and handle the complexity in code.…