Start with the connection you need
An agent system may need both access to external tools and a way to work with another agent. These are different integration problems. Choosing a protocol starts with identifying which boundary your application needs to cross.
Where MCP fits
The Model Context Protocol defines a standard way for AI applications to connect to external systems. Think of an assistant that needs access to a document source or a tool: MCP provides a shared integration model rather than a custom connector for every combination.
Where A2A fits
The Agent2Agent protocol concerns communication and collaboration between agents. Its documentation covers discovery and task-oriented interaction. This can matter when separate agent services need to cooperate rather than simply expose a tool call.
What to check before adoption
Read the protocol version, authentication model, and supported capabilities of each implementation. A product described as an AI agent is not automatically A2A-compatible, and a framework listing is not proof of interoperability. AINavly does not assign compatibility badges without implementation evidence.
Sources & editorial note
This introduction draws on the official resources below. It is not a hands-on benchmark. Product capabilities can change; check the linked documentation before implementation.
