A2A Protocol
A2A (Agent2Agent) Protocol is an open interoperability protocol developed by Google that enables seamless communication and collaboration between AI agents across different frameworks and vendors, regardless of their underlying architecture.
https://github.com/google/A2A?ref=aipure
Product Information
Updated:Apr 11, 2025
What is A2A Protocol
Agent2Agent (A2A) Protocol is Google's open-source initiative designed to address one of the biggest challenges in enterprise AI adoption - enabling AI agents built on different frameworks and vendors to work together effectively. The protocol provides a standardized way for agents to communicate, share capabilities, and coordinate tasks while maintaining security. It complements Anthropic's Model Context Protocol (MCP) by focusing on agent-to-agent level interactions rather than individual language model operations. With support from over 50 technology partners including major players like Salesforce, SAP, ServiceNow, and MongoDB, A2A aims to establish a universal framework for agent communication in the enterprise environment.
Key Features of A2A Protocol
A2A (Agent2Agent) Protocol is an open-source protocol developed by Google that enables seamless communication and interoperability between AI agents across different frameworks and vendors. It provides a standardized way for agents to discover capabilities, manage tasks, exchange multi-modal content, and coordinate complex workflows while maintaining enterprise-grade security and real-time synchronization features.
Agent Discovery and Capability Advertisement: Agents can publish their capabilities via JSON-formatted Agent Cards, allowing other agents to discover and identify the most suitable partners for specific tasks
Standardized Task Management: Provides unified methods for sending, getting, and canceling tasks, with support for long-running operations and real-time status updates through streaming and push notifications
Multi-modal Content Support: Enables exchange of various content types including text, files, structured data, audio, and video through Parts and Artifacts system
Enterprise-Grade Security: Built-in security features for authentication, authorization, and encryption, ensuring secure agent communication in enterprise environments
Use Cases of A2A Protocol
Complex Workflow Automation: Orchestrating multi-stage business processes like supply chain planning or recruitment workflows across different AI agents and systems
Cross-Platform Integration: Enabling seamless communication between AI agents built on different platforms like Salesforce, SAP, and ServiceNow for unified enterprise operations
Collaborative Problem Solving: Multiple specialized AI agents working together to solve complex tasks, such as document processing, data analysis, and decision-making
Pros
Open-source and vendor-neutral, promoting wide adoption and community contribution
Built on established standards (HTTP/JSON) for easy integration with existing systems
Enterprise-ready with robust security features and long-task support
Cons
Still in early stages with adoption not yet at tipping point
Competing protocols (like AGNTCY) may fragment the market
How to Use A2A Protocol
Step 1: Understand Core Concepts: Familiarize yourself with key A2A concepts like Agent Cards, A2A Server/Client, Tasks, Messages, Parts, Artifacts, Streaming and Push Notifications
Step 2: Read Documentation: Review the technical documentation at google.github.io/A2A and JSON specification at github.com/google/A2A/blob/main/specification
Step 3: Set Up Agent Card: Create an agent.json metadata file at /.well-known/agent.json describing your agent's capabilities, skills, endpoint URL and authentication requirements
Step 4: Implement A2A Server: Set up an HTTP endpoint that implements the A2A protocol methods using sample implementations in Python or JavaScript from the GitHub repository
Step 5: Create A2A Client: Build a client application that can discover agents via Agent Cards and send requests to A2A servers using the provided client libraries
Step 6: Initialize Communication: Have your client fetch the Agent Card, then send tasks/send or tasks/sendSubscribe requests with messages to initiate agent communication
Step 7: Handle Task Lifecycle: Implement logic to track task states (submitted, working, input-required, completed, etc) and handle streaming updates or push notifications if supported
Step 8: Test Integration: Use the provided sample agents and demo web app to test your A2A implementation and verify interoperability
Step 9: Add Advanced Features: Optionally implement additional capabilities like streaming, push notifications, or multi-agent collaboration based on your needs
Step 10: Deploy and Monitor: Deploy your A2A-enabled agents to production and monitor their communication and task execution
A2A Protocol FAQs
A2A (Agent2Agent) Protocol is an open protocol created by Google that enables communication and interoperability between AI agents built on different frameworks and vendors. It provides a common language for agents to communicate with each other regardless of their underlying technology.
A2A Protocol Video
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