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AI Tool
A2A Review
Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.
1Initially launched by Google in April 2025 with over 50 technology partners.
2Now an open-source project under the Linux Foundation.
3Reached version 1.0, its first stable specification, by April 2026.
4Supported by over 150 organizations as of April 2026, with deep integration across Google, Microsoft, and AWS platforms.
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A2A at a Glance
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About A2A
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overview
What is A2A?
A2A is an open protocol developed by Google (now open-source under the Linux Foundation) that enables AI Agent Developers and System Architects to facilitate communication and interoperability between opaque agentic applications. It acts as a universal communication standard, allowing AI agents to discover capabilities, exchange information, and coordinate actions across diverse platforms. The Agent2Agent (A2A) Protocol was officially launched by Google in April 2025 and subsequently donated to the Linux Foundation, becoming an open-source project. This protocol addresses the challenge of interoperability in multi-agent systems, where agents built by different teams or vendors need to work together to achieve complex goals. By April 2026, A2A had reached version 1.0, its first stable specification, marking it as a production-ready open standard. As of April 2026, over 150 organizations support the A2A standard, with active production deployments in various industries.
quick facts
Quick Facts
| Attribute | Value |
|---|---|
| Developer | Google (now Linux Foundation) |
| Business Model | Open Source |
| Pricing | Freemium |
| Platforms | API |
| API Available | Yes |
| Founded | April 2025 (initial launch) |
features
Key Features of A2A
The A2A Protocol provides a robust set of features designed to standardize and secure communication within multi-agent AI systems, enabling complex interactions and workflows.
- 1Enabling communication and interoperability between opaque agentic applications.
- 2Seamless communication and collaboration between AI agents, regardless of underlying frameworks or vendors.
- 3Secure and opaque collaboration between agents without sharing internal logic or proprietary data.
- 4Standardized communication and collaboration between AI agents through an open protocol.
- 5Interoperability between AI agents built on different platforms and frameworks.
- 6Facilitating complex workflows with sub-task delegation and action coordination among agents.
- 7Supporting long-running tasks with real-time feedback and state updates.
- 8Enabling agents to discover each other's capabilities dynamically.
- 9Standardizing agent discovery, secure task delegation, and progress streaming (Version 0.3.0).
- 10Support for structured outputs in agent communications.
use cases
Who Should Use A2A?
A2A is primarily designed for stakeholders involved in the development, architecture, and deployment of advanced AI agent systems that require robust interoperability and collaboration.
- 1AI Agent Developers: For building robust multi-agent systems, ensuring interoperability across different frameworks, and enabling agents to delegate sub-tasks and coordinate actions.
- 2AI Agent System Architects: For designing scalable, secure, and standardized multi-agent architectures that require seamless communication between diverse AI agents.
- 3Businesses deploying multi-agent AI systems: To automate complex enterprise workflows (e.g., supply chain planning, loan processing), enhance customer experience, and reduce integration complexity across various applications and siloed data systems.
- 4Organizations requiring secure and opaque collaboration: For scenarios where agents need to interact and exchange information without exposing internal logic or proprietary data.
pricing
A2A Pricing & Plans
A2A operates on a freemium model, with its core protocol being open-source under the Linux Foundation. This allows developers and organizations to implement and utilize the standard without direct licensing costs. Any associated costs would typically arise from the infrastructure required to host and operate agents that adhere to the A2A protocol, or from commercial services built on top of the open standard.
- 1Open-source core: Free to implement and use the A2A protocol standard.
- 2Commercial implementations: Pricing varies based on vendor-specific offerings and managed services, such as Google Cloud's Vertex AI Agent Engine integration, which provides a standardized, scalable, and managed solution for building multi-agent systems.
competitors
A2A vs Competitors
A2A is positioned as a foundational communication protocol within the AI agent ecosystem, often complementing rather than directly competing with other tools and frameworks. Its primary focus is on standardizing agent-to-agent communication.
1
Agent Communication Protocol (ACP)↗
An open standard for agent-to-agent communication, designed for simplicity, flexibility, and vendor neutrality, with a focus on RESTful, HTTP-based interfaces.
Like A2A, ACP is an open standard for agent-to-agent communication under the Linux Foundation; however, ACP is merging its technology and expertise into A2A. It also uses HTTP and REST conventions, similar to A2A's foundation on HTTP and JSON-RPC.
2
Agent Network Protocol (ANP)↗
Aims to be 'the HTTP of the agentic web era' with a peer-to-peer architecture, using HTTP for data transport and JSON-LD for data formatting.
ANP is another open-source protocol for agent communication, similar to A2A in its goal of standardizing agent interaction, but it emphasizes a peer-to-peer architecture and JSON-LD for data formatting.
3
Agent Protocol↗
An open API specification that enables seamless communication with AI agents, regardless of framework, language, or platform, defined using OpenAPI.
Agent Protocol provides a universal API specification for agent communication, similar to A2A's goal of interoperability, but focuses on a REST API with core endpoints for task and step management.
4
AutoGen↗
An open-source framework from Microsoft for building multi-agent AI applications, emphasizing conversational interactions and robust support for code generation and execution.
AutoGen is a comprehensive framework for building multi-agent systems, whereas A2A is a protocol for communication between agents; AutoGen provides the environment and tools to *create* agents that would then potentially use protocols like A2A for external communication. AutoGen handles orchestration and communication within its framework, offering a more complete solution for multi-agent development compared to A2A's protocol-level focus.
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Frequently Asked Questions
+What is A2A?
A2A is an open protocol developed by Google (now open-source under the Linux Foundation) that enables AI Agent Developers and System Architects to facilitate communication and interoperability between opaque agentic applications. It acts as a universal communication standard, allowing AI agents to discover capabilities, exchange information, and coordinate actions across diverse platforms.
+Is A2A free?
Yes, the core A2A protocol is open-source under the Linux Foundation and is free to implement and use. However, costs may arise from the infrastructure required to host and operate agents adhering to the protocol, or from commercial services and managed solutions built on top of the open standard, such as Google Cloud's Vertex AI Agent Engine.
+What are the main features of A2A?
A2A's main features include enabling communication and interoperability between opaque agentic applications, facilitating seamless and secure collaboration between AI agents without sharing internal logic, standardizing communication across different platforms, supporting complex workflows with sub-task delegation, and allowing agents to discover each other's capabilities for long-running tasks with real-time feedback.
+Who should use A2A?
A2A is intended for AI Agent Developers building multi-agent systems, AI Agent System Architects designing scalable agent infrastructures, and businesses deploying multi-agent AI systems to automate complex enterprise workflows, enhance customer experience, and reduce integration complexity across diverse applications.
+How does A2A compare to alternatives?
A2A primarily focuses on horizontal agent-to-agent communication, distinguishing it from protocols like MCP (Model Context Protocol) which focus on vertical application-to-model integration. It is consolidating with ACP (Agent Communication Protocol) and differs from frameworks like AutoGen, which provide environments for building agents rather than just communication standards. Other protocols like ANP and Agent Protocol also aim for agent communication but may emphasize different architectural approaches or API specifications.