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2026-05-11mcpa2aprotocol

MCP vs A2A: the two protocols every AI builder needs to understand

The agentic era runs on two complementary protocols. MCP (Model Context Protocol) connects agents to tools and data. A2A (Agent-to-Agent) connects agents to other agents. Understanding the difference — and when to use which — is essential in 2026.

MCP
Model Context Protocol
  • • Agent → Tool communication
  • • “Call this API with these params”
  • • 10,000+ public servers
  • • 97M monthly SDK downloads
  • • Linux Foundation (AAIF)
  • • Anthropic, OpenAI, Google, AWS
A2A
Agent-to-Agent Protocol
  • • Agent → Agent communication
  • • “Delegate this task to specialist”
  • • 150+ orgs in production
  • • Google ADK native support
  • • Peer-to-peer task delegation
  • • Multi-framework interop

They’re complementary, not competing

MCP is vertical: agent reaches down to tools and data. A2A is horizontal: agents communicate with peers. A financial analysis agent might use MCP to call apitree’s search_apis for market data, while using A2A to delegate report formatting to a writing agent.

Layered Protocol Stack
Your App
A2A
agent↔agent
MCP
agent↔tool
apitree
1,950+ APIs

Where apitree sits

apitree is a MCP-native platform. When an agent (from any framework — LangGraph, CrewAI, AutoGen) needs external data, it connects to apitree via MCP. apitree handles the last mile: auth, proxy, cache, billing. The agent doesn’t need to know whether the data comes from OpenAI, a Korean government API, or a free public endpoint.

In a multi-agent A2A system, apitree becomes the shared infrastructure layer. Agent A calls agent B via A2A; agent B calls apitree via MCP for data. Both protocols working together.

Sources: OneReach Protocol Guide, InfoQ A2A+MCP Architecture, freeCodeCamp Multi-Agent Book

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