MCP, A2A and function calling each solve a different layer of agent systems
goyalshaliniuk · x · 2026-07-21
A concise explainer breaks down how MCP, A2A, and function calling solve different parts of LLM and agent systems. - **MCP** is framed as a way to manage dynamic context windows in enterprise LLM infrastructure, pulling in memory, history, and metadata to personalize responses without hardcoding prompt logic. - **A2A** is described as direct communication between agents through a shared protocol, useful for collaboration in multi-agent systems. - **Function calling** is presented as task execution: the model acts like a planner, decomposes work into a DAG of subtasks, and routes each one to tools such as math, search, or APIs. - The post concludes that mastering all three is important for production-ready AI systems.
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