Google has unveiled the Agent2Agent (A2A) framework, designed to enhance communication and collaboration among independent AI agents across various systems.

Focusing on security and efficiency, A2A incorporates enterprise-grade authentication and supports various modalities, including text, audio, and video.

A2A and the Model Context Protocol (MCP) are complementary, with A2A enabling collaborative problem-solving and MCP focusing on precise tool execution.

The primary goal of A2A is to address interoperability challenges among AI agents from different vendors, enabling them to work together efficiently.

The protocol supports complex multi-agent workflows, exemplified by its use in recruitment processes where multiple agents coordinate tasks.

A2A introduces a task object that monitors processes and outputs, facilitating effective management of both immediate and long-running tasks.

As an open standard protocol, A2A allows different AI agents to interact seamlessly, similar to how the web connects diverse services regardless of their underlying technology.

Communication between agents occurs through structured messages that can include context, instructions, and outputs from completed tasks.

Recent updates include Google's commitment to open-source development for A2A, the introduction of the Agent Development Kit, and various new product releases related to AI.

In A2A, the fundamental unit of work is a 'Task,' which a client agent initiates and sends to a remote agent for execution, with the result termed an 'Artifact.'

The development of A2A has been backed by over 50 partners, including major technology companies like Atlassian and Salesforce, highlighting its collaborative approach to agent interoperability.

By promoting open-source contributions, Google aims to foster innovation and community engagement in the AI space through the A2A framework.