A2A vs MCP: how they overlap and differ
Blog post from Merge
The provided text discusses the differences and functionalities of two open standard protocols, the Agent-to-Agent (A2A) protocol and the Model Context Protocol (MCP). A2A, developed by Google, facilitates communication between AI agents by allowing a client agent to request tasks from a remote agent, which can be used for workflows such as autonomous lead routing. MCP, from Anthropic, focuses on enabling large language models (LLMs) to interact with third-party applications, such as integrating LLMs with applicant tracking systems to enhance recruiting processes. Despite both protocols being used to automate workflows, they serve different purposes, with A2A prioritizing interoperability between AI agents and MCP enhancing LLM interactions with external data sources. Additionally, the text mentions Merge's role as an integration platform offering Unified API products to manage customer integrations and control AI agents.
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