A2A vs MCP: Here's How To Choose The Right Protocol👇 Google just open-sourced the Agent-to-Agent (A2A) protocol—and it might be the biggest thing to hit the agent ecosystem since LangChain dropped tools. This isn’t about A2A replacing Model Context Protocol (MCP). This is about interoperability and division of labor. ➡️MCP is a lightweight protocol that standardizes tool use for LLM-based agents. Core Components: 1. MCP Host: Where the LLM sits. Can call tools via MCP. 2. MCP Server: A container for capabilities (tools, APIs). 3. MCP Client: Communicates 1:1 with servers. 💡Data Sources: Local + remote, accessed via MCP. ➡️Where MCP stops at "tool use," A2A steps in for inter-agent communication. What it adds: 1. Secure identity and trust layer (auth missing in MCP) 2. Shared task + state negotiation 3. Dynamic capability discovery 4. Intent-based UX protocol 💡In short: A2A enables multi-agent cognition. Think swarms, not silos. ➡️The twist? You can run both. An agent can be an MCP host and A2A-compliant communicator. This is where it gets interesting: protocols as composable infrastructure layers. ➡️To summarize: MCP gives you tool access. A2A gives you autonomy and coordination. Which protocol becomes the standard depends on adoption velocity, ecosystem tooling, and... maybe a bit of politics. If you’re building agent-first architectures, which one’s your foundation layer—and why? Credits: Aurimas Griciūnas #a2a #mcp #llm #aiagent #machinelearning | 39 comments on LinkedIn