Agent to Agent Protocol
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MCP (Model Context Protocol) and A2A (Agent-to-Agent Protocol) serve different purposes and work in distinct ways.
🧩 MCP (Model Context Protocol) • Purpose: Enables a single AI model to interact with external tools and data sources • How it works: Uses precise, structured function calls to connect with APIs and tools • Best for: Predictable, well-defined tasks like data retrieval, calculations, or search
🤖 A2A (Agent-to-Agent Protocol) • Purpose: Allows multiple AI agents to collaborate asynchronously by sharing tasks and outputs • How it works: Supports flexible task delegation and coordination in multi-agent environments • Best for: Complex workflows where autonomous agents need to solve problems together
✅ Summary • MCP: Enhances individual agent capabilities • A2A: Enables collaboration between multiple agents
Google introduced the Agent2Agent (A2A) protocol, an open standard enabling seamless communication and collaboration between AI agents from different frameworks or vendors, aimed at solving interoperability challenges in enterprise AI systems.