Artificial intelligence is moving away from experimental prototypes to mission-critical enterprise-level infrastructure. Creating systems that work under the constraints and requirements present in the enterprise world has never been more challenging for developers. There are three innovative architectural patterns that will define production-grade AI solutions: model-context protocol (MCP), agent-to-agent Protocol (A2A), and functional calling.
Model-Context Protocol (MCP): Context Execution Modality
LLMs are limited in their handling of state, memory specific to the application, and context window. MCP addresses these issues by treating context as an architectural component. In MCP, context is not static but dynamic, based on sophisticated retrieval that injects the relevant data just in time.