LLM Context Protocols: Agent2Agent vs. MCP
Blog post from Stream
The discussion revolves around two emerging protocols in AI development, Model Context Protocol (MCP) and Agent2Agent (A2A), which are transforming how AI models interact with external services and each other. MCP, established in 2024, facilitates interaction between AI agents and external tools, focusing on instruction-based tasks, while A2A, launched by Google in 2025, enables communication between multiple agents for collaborative, goal-oriented tasks. These protocols aim to overcome the limitations of previous integration methods, such as function calling and ChatGPT plugins, which lacked standardization across different platforms. MCP and A2A are designed to be complementary, with MCP offering a structured approach to tool integration and A2A providing flexibility and platform independence for multi-agent collaboration. This synergy allows agents to not only access specialized tools but also discover and negotiate tasks among themselves, thereby enhancing the adaptability and capability of AI applications. As AI technology progresses, the integration of both protocols is expected to create more robust, reliable, and collaborative AI systems, with ongoing developments potentially expanding their functionalities to facilitate further inter-agent communication and cooperation.