As AI agents become integral to modern applications, standardized communication protocols are essential. Google's Agent2Agent (A2A) Protocol and Anthropic's Model Context Protocol (MCP) address this need from different angles. A2A focuses on inter-agent collaboration, while MCP standardizes interactions between agents and external tools.
Understanding the Protocols
Agent2Agent (A2A) Protocol
Developed by Google, A2A enables AI agents to communicate and collaborate across various frameworks and platforms. It uses JSON-RPC 2.0 over HTTP(S) and supports Server-Sent Events (SSE) for streaming updates. Agents publish "Agent Cards"—JSON metadata documents detailing their capabilities—to facilitate discovery and task delegation.
Model Context Protocol (MCP)
MCP, introduced by Anthropic, provides a standardized way for AI agents to interact with external tools and data sources. Built on JSON-RPC 2.0, MCP supports stateful, bidirectional communication, allowing agents to maintain context over multiple interactions. It includes features like tool discovery, access control, and streaming responses.
Feature Comparison
| Aspect | Agent2Agent (A2A) | Model Context Protocol (MCP) |
|---|---|---|
| Purpose | Direct agent-to-agent collaboration | Tool access and context preservation |
| Architecture | Decentralized, peer-to-peer | Centralized orchestration |
| Transport | HTTP + JSON-RPC + SSE | HTTP + JSON-RPC + streaming |
| Discovery | Agent Cards | Tool manifests |
| Context | Stateless interactions | Context memory support |
| Security | Token auth, flexible policies | Scoped permissions |
Use Case Recommendations
- A2A: Multi-agent systems, self-organizing AI, distributed decision-making
- MCP: Secure tool usage, memory-augmented agents, enterprise API integrations
Conclusion
Both A2A and MCP offer essential solutions to modern agent-based systems. A2A facilitates agent-to-agent collaboration in open networks, while MCP strengthens how LLMs connect with tools. Most future systems may use both protocols together to balance flexibility with control.