A2A (Agent-to-Agent) and MCP (Model Context Protocol) are two complementary open standards for AI agent systems that operate at different layers. A2A standardizes how autonomous agents discover each other, delegate tasks, stream updates, and authenticate peer-to-peer. MCP standardizes how AI applications and agents connect to external tools, resources, APIs, and prompts via a host-client-server model using JSON-RPC. The two protocols are not competing: A2A handles inter-agent orchestration and delegation, while MCP handles tool and context integration. Complex systems often use both together — a planner agent delegates via A2A to specialist agents that internally use MCP to call tools. The post covers their differences in a comparison table, security considerations, pros/cons, Python code examples, and a real-world customer support workflow.
Table of contents
Key TakeawaysWhat Is A2A (Agent‑to‑Agent)?What Is MCP (Model Context Protocol)?Key Differences Between A2A and MCPSecurity ConsiderationsPros and Cons of A2A and MCPFAQ SECTIONConclusionReferences and ResourcesSort: