A2A and MCP are often discussed together because both help connect AI systems, but they solve different integration problems. MCP standardizes how an AI application connects to tools and context. A2A standardizes how independently built agents can discover and collaborate with one another.
What MCP is for
An MCP client connects an AI host to an MCP server that exposes capabilities such as tools, resources or prompts. This is a useful boundary between a model-facing application and the services or data it can use. The host remains responsible for user experience and deciding which capabilities are allowed.
What A2A is for
A2A is designed for communication between agents, including agents built with different frameworks or operated by different services. Its concepts support describing an agent's capabilities and exchanging work with it. That makes A2A useful when the other participant is not simply a tool the caller owns, but a separate agent that can carry out a task.
A simple example
Imagine a travel-planning agent. It could use MCP to read a user's permitted preferences or query an internal booking tool. It could use A2A to delegate a research task to a separately operated destination-information agent. The exact division depends on product ownership, trust and deployment boundaries—not on which protocol is newer.
They are complementary, not competing
A practical architecture can use both: MCP at the agent-to-tool boundary and A2A at the agent-to-agent boundary. Neither protocol automatically solves authentication policy, user consent, tool correctness or business-level transaction guarantees. Those remain application and deployment design concerns.
Where Agent Communication Protocol fits
The acronym ACP is overloaded. The Agent Communication Protocol maintained by the BeeAI community announced that it is now part of A2A under the Linux Foundation. That is distinct from the Agentic Commerce Protocol, which describes buyer-agent-merchant checkout. When searching for ACP documentation, check the expanded name and project before assuming the topic.
Choose by participant and responsibility
Use MCP when an AI host needs a structured connection to a capability or context provider. Use A2A when a separate agent needs to receive or collaborate on a task. In either case, define authorization, timeouts, error handling and human approval explicitly at your application boundary.