The Model Context Protocol (MCP), Agent Communication Protocol (ACP), and Agent2Agent Protocol (A2A) are three protocols designed to power the interactions of agents in various AI applications. MCP is an open protocol focused on standardizing how LLM-based applications connect to data sources and tools, providing a standardized way to provide context and functionality to large language models. ACP is IBM Research's agent-to-agent communication standard, powering multi-agent workflows within BeeAI, an experimental platform that makes it easy to run and orchestrate open-source AI agents. A2A is Google's open protocol designed specifically for agent interoperability across frameworks, allowing agents from different frameworks to discover each other's capabilities, exchange messages, and collaborate on tasks. Each protocol has its primary goal, core elements, and use cases, with MCP focusing on standardizing data access, ACP on orchestrating local multi-agent environments, and A2A on bridging cross-vendor agent ecosystems. Understanding the strengths of each protocol can help developers pick the right tool for their agent architecture.