Decoding LLM Magic: RAG, Function Calling, and MCP Explained!

This article beautifully breaks down three key techniques for supercharging your Large Language Model (LLM) applications: Retrieval-Augmented Generation (RAG), Function Calling, and Model Context Protocol (MCP). It clarifies their unique mechanisms, workflows, and ideal use cases, giving developers a clear roadmap for integrating external knowledge and tools into their AI systems.

• •RAG enhances LLMs by retrieving relevant information before generating answers, ideal for handling extensive static documents.
• •Function Calling empowers LLMs to decide which functions to execute, with the application handling the actual execution.
• •MCP standardizes the use of external tools, enabling LLMs to leverage them during answer generation.