MCP vs A2A (Agent2Agent) protocol, clearly explained:
Agentic applications require both A2A and MCP.
- MCP provides agents with access to tools.
- While A2A allows agents to connect with other agents and collaborate in teams.
Today, I'll clearly explain what A2A is and how it can work with MCP.
**What is A2A? **
A2A (Agent-to-Agent) enables multiple AI agents to work together on tasks without directly sharing their internal memory, thoughts, or tools.
Instead, they communicate by exchanging context, task updates, instructions, and data.
A2A vs MCP
AI applications can model A2A agents as MCP resources, represented by their AgentCard (more about cards in next tweet).
Using this AI agents connecting to an MCP server can discover new agents to collaborate with and connect via the A2A protocol.
Agent Cards ( ID cards for Agents )
A2A-supporting Remote Agents must publish a JSON Agent Card detailing their capabilities and authentication.
Clients use this to find and communicate with the best agent for a task.
What makes A2A powerful?
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Secure collaboration
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Task and state management
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UX negotiation
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Capability discovery
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Agents from different frameworks working together
Additionally, it can integrate with MCP.
While it's still new, it's good to standardize Agent-to-Agent collaboration, similar to how MCP does for Agent-to-tool interaction.
What are your thoughts ?
Here's a graphic summarising our discussion.
author:https://x.com/akshay_pachaar