Ask HN: Can someone ELI5 how Google's A2A is different from MCP?
2 comments
MCP (Model Context Protocol) is essentially a protocol for tool access. It defines a standard way for large language models to interact with various tools, data, and resources. Simply put, MCP enables AI to use various functionalities, much like how programmers call functions.
A2A (Agent-to-Agent Protocol) focuses on agent collaboration. It establishes ways for intelligent agents to discover, communicate, and cooperate with each other, allowing different AI systems to work together like human teams.
Taken straight from this article:
https://a2aprotocol.ai/blog/a2a-vs-mcp
A2A (Agent-to-Agent Protocol) focuses on agent collaboration. It establishes ways for intelligent agents to discover, communicate, and cooperate with each other, allowing different AI systems to work together like human teams.
Taken straight from this article:
https://a2aprotocol.ai/blog/a2a-vs-mcp
it still didn't click me.
Let's say I have 2 agents which uses 2 APIs under the hood: - Agent A: uses API A1 and A2 through MCP - Agent B: uses API B1 and B2 through MCP
Assumption here is that, Agent A can't access APIs B1 and B2 but can access Agent B. What if I expose Agent B as an MCP server. Why do I need A2A?
Let's say I have 2 agents which uses 2 APIs under the hood: - Agent A: uses API A1 and A2 through MCP - Agent B: uses API B1 and B2 through MCP
Assumption here is that, Agent A can't access APIs B1 and B2 but can access Agent B. What if I expose Agent B as an MCP server. Why do I need A2A?
The simple answer is it is Google that alone should make it easy to understand.
They can't monetize a MCP API so they made A2A.
They can't monetize a MCP API so they made A2A.
In my mind, I am still designing things with MCP. Even the communication between 2 agents can modeled as MCP with some capabilities.