Explore Google A2A: The Future of AI Agent Collaboration
An open protocol connecting AI agents, empowering enterprise innovation through seamless collaboration
Core A2A Capabilities
The Agent2Agent protocol enables AI systems to work together through standardized communication and task coordination.
Capability Discovery
Agents dynamically identify and share abilities through standardized Agent Cards, enabling flexible collaboration.
Task Management
Structured workflow for task delegation, progress monitoring, and result verification between collaborative agents.
Secure Collaboration
Integrated security standards for authenticated agent interactions with permission controls and data protection.
What is Google A2A?
The Agent2Agent (A2A) Protocol is Google's open standard for enabling AI assistants to communicate and collaborate effectively. Unlike other approaches, A2A focuses on standardized discovery and task delegation between diverse AI systems.
By providing a common language for agent interactions, A2A enables seamless integration across platforms, vendors, and technologies—unlocking new possibilities for enterprise automation and innovation.
How A2A Works
Follow the A2A workflow process that enables effective agent communication and collaboration
Discovery
Agents identify capabilities through standardized Agent Cards
Task Creation
Tasks defined with clear inputs, outputs and success criteria
Execution
Target agent processes task with status updates
Completion
Results delivered with artifacts and verification
Latest Updates
Stay informed with the latest developments in the A2A ecosystem
Announcing the Agent2Agent Protocol (A2A)
Google introduces the open A2A protocol for enabling seamless communication between AI agents across platforms.
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Major Partners Join A2A Initiative
Leading technology companies announce support for Google's A2A protocol to advance agent interoperability.
Read more
Getting Started with Google A2A: Tutorial Released
A comprehensive hands-on tutorial for developers to implement the Agent2Agent protocol in their applications.
Read moreFeatured A2A Agents & Platforms
Discover AI systems implementing the A2A protocol for enhanced collaboration
LangGraph Currency Agent
AgentA specialized agent supporting multi-turn conversations for currency conversion and financial calculations.
Salesforce Agentforce
PlatformEnterprise AI platform integrating A2A for seamless CRM automation and cross-platform collaboration.
A2A in Action
Explore how organizations are implementing A2A to solve real business challenges
Recruitment Automation
HRAI agents collaborate to screen resumes, schedule interviews, and provide candidate insights through A2A communication.
View case studyHealthcare Coordination
HealthcareSpecialized medical agents share patient data and treatment recommendations while maintaining privacy compliance.
View case studyRetail Intelligence
RetailSales forecasting, inventory management, and customer service agents working together through A2A protocol.
View case studyTechnical Documentation
Comprehensive resources to help developers implement A2A protocol in their applications. Get started with our guides, API references, and examples.
Protocol Specs
Detailed A2A protocol specifications and standards
Key Concepts
Agent Cards, Tasks, Artifacts and lifecycle management
Developer Guide
Step-by-step tutorials with Python and JavaScript examples
API Reference
Complete API documentation for A2A implementation
# A2A Protocol Example: Task Creation
import a2a
# Initialize agents
source_agent = a2a.Agent(
name="TaskManager",
description="Coordinates project tasks"
)
target_agent = a2a.Agent(
name="DataAnalyst",
card_url="https://agents.example.com/cards/analyst"
)
# Create task with parameters
task = source_agent.create_task(
target=target_agent,
name="quarterly_analysis",
description="Analyze Q2 sales performance",
input_parameters={
"data_source": "sales_q2_2025.csv",
"metrics": ["revenue", "growth", "conversion"]
},
expected_output={
"format": "dashboard",
"charts": ["trend", "comparison"]
}
)
# Submit task and await results
response = source_agent.submit(task)
task_id = response.task_id
# Check status
status = source_agent.check_status(task_id)
print(f"Task status: {status.state}")
Join the A2A Community
Connect with developers, share insights, and contribute to the evolution of agent collaboration
GitHub Discussions
Join technical discussions, report issues, and contribute to A2A development
Visit GitHubX (Twitter)
Follow #A2AProtocol for the latest updates, news, and community highlights
Join the ConversationPartner Ecosystem
Frequently Asked Questions
Common questions about the A2A protocol and implementation
What is the difference between A2A and MCP?
A2A (Agent2Agent) is Google's protocol focusing on standardized discovery and task delegation between diverse AI systems, while MCP (Machine Communication Protocol) by Anthropic emphasizes message-based communication between specialized AI agents. A2A provides more structured task management and agent capability discovery.
How do I create an Agent Card for my AI system?
Agent Cards are JSON documents describing an agent's capabilities, inputs, outputs, and interaction protocols. You can create one by following the A2A specification guidelines in our documentation, which includes JSON schemas, validation tools, and examples. The card should be hosted at a public URL for discovery by other agents.
What programming languages are supported for A2A implementation?
A2A is language-agnostic, with official SDK support for Python and JavaScript. Community implementations exist for Java, Go, and C#. Any language capable of making HTTP requests and processing JSON can implement the A2A protocol. Check our GitHub repository for the latest language bindings and examples.
What are the costs associated with using A2A?
The A2A protocol is open source and free to use under the Apache 2.0 license. There are no licensing fees for implementation. However, depending on your deployment, you may incur costs related to cloud resources, infrastructure, or specific AI services you integrate with your A2A-enabled systems.
Ready to Implement A2A?
Start building collaborative AI systems with the Agent2Agent protocol today