Agent Interoperability Protocols

AI agents are software systems that perceive their environment, reason about goals, and take actions to achieve those goals. As organizations deploy more agents across different frameworks, platforms, and vendors, these agents need to share context, discover each other's capabilities, delegate tasks, and coordinate work. Agent interoperability protocols define the standards that make this possible.

The Problem

Before interoperability protocols, every AI application needed custom integration code for each data source, tool, and external agent it wanted to use. A coding assistant that needed access to a database, a file system, and a search engine would require three separate integrations, each with its own authentication, data formats, and error handling. When a second assistant from a different vendor joined the environment, the process repeated.

This approach does not scale. Organizations end up with N agents times M integrations, where most of the work is duplicated rather than focused on the actual agent capabilities. Worse, agents cannot discover what other agents can do, so they cannot delegate tasks or collaborate without human configuration.

What Agent Interoperability Protocols Provide