Interoperability is essential for AI agents in enterprise environments, allowing them to securely share tools, context, and tasks across various platforms. Currently, many AI agents operate in isolation within specific systems—such as Workday, Oracle, or Jira—leading to inefficiencies and redundant efforts. To tackle the last-mile problem of enterprise AI, open protocols like Model Context Protocol (MCP) and Agent-to-Agent (A2A) are crucial. MCP enables seamless communication between models and tools, while A2A facilitates interaction between different agents, allowing them to discover capabilities and delegate tasks. For optimal performance, enterprises need standardized data models, secure connection protocols, and context-aware permissions. By prioritizing interoperability, organizations can move beyond fragmented systems to create a cohesive, scalable AI ecosystem. Addressing interoperability now is vital for maximizing the potential of enterprise AI agents.
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