Still confused between MCP, A2A, and Functional Calling? These three approaches are reshaping how LLMs and agents operate at scale, but each one solves a very different problem. Let’s break it down 👇 1. Model-Context Protocol (MCP) MCP manages dynamic context windows across enterprise LLM infrastructure. It retrieves prior memory, history, and metadata to personalize every response without hardcoding logic into prompts. 2. Agent-to-Agent Protocol (A2A) In A2A, agents talk to each other directly using shared protocols. Think of it as collaborative problem-solving between specialized local agents, especially useful in multi-agent ecosystems. 3. Functional Calling Here, an LLM acts like a planner. It decomposes a task (e.g., comparing market caps), generates a Directed Acyclic Graph (DAG) of subtasks, and then sends each task to appropriate tools (math, search, APIs) for execution. Conclusion - MCP is about managing context, - A2A is about agent collaboration, - Functional Calling is about task execution. Mastering all three is key to building powerful, production-ready AI systems. Save this visual for your next AI project! | 26 comments on LinkedIn