crewAI/docs/concepts/a2a-integration.md

A2A Protocol Integration

CrewAI supports the A2A (Agent-to-Agent) protocol, enabling your crews to participate in remote agent interoperability. This allows CrewAI crews to be exposed as remotely accessible agents that can communicate with other A2A-compatible systems.

Overview

The A2A protocol is Google's standard for agent interoperability that enables bidirectional communication between agents. CrewAI's A2A integration provides:

• Remote Interoperability: Expose crews as A2A-compatible agents
• Bidirectional Communication: Enable full-duplex agent interactions
• Protocol Compliance: Full support for A2A specifications
• Transport Flexibility: Support for multiple transport protocols

Installation

A2A support is available as an optional dependency:

pip install crewai[a2a]

Basic Usage

Creating an A2A Server

from crewai import Agent, Crew, Task
from crewai.a2a import CrewAgentExecutor, start_a2a_server

# Create your crew
agent = Agent(
    role="Assistant",
    goal="Help users with their queries",
    backstory="A helpful AI assistant"
)

task = Task(
    description="Help with: {query}",
    agent=agent
)

crew = Crew(agents=[agent], tasks=[task])

# Create A2A executor
executor = CrewAgentExecutor(crew)

# Start A2A server
start_a2a_server(executor, host="0.0.0.0", port=10001)

Custom Configuration

from crewai.a2a import CrewAgentExecutor, create_a2a_app

# Create executor with custom content types
executor = CrewAgentExecutor(
    crew=crew,
    supported_content_types=['text', 'application/json', 'image/png']
)

# Create custom A2A app
app = create_a2a_app(
    executor,
    agent_name="My Research Crew",
    agent_description="A specialized research and analysis crew",
    transport="starlette"
)

# Run with custom ASGI server
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8080)

Key Features

CrewAgentExecutor

The CrewAgentExecutor class wraps CrewAI crews to implement the A2A AgentExecutor interface:

• Asynchronous Execution: Crews run asynchronously within the A2A protocol
• Task Management: Automatic handling of task lifecycle and cancellation
• Error Handling: Robust error handling with A2A-compliant responses
• Output Conversion: Automatic conversion of crew outputs to A2A artifacts

Server Utilities

Convenience functions for starting A2A servers:

• start_a2a_server(): Quick server startup with default configuration
• create_a2a_app(): Create custom A2A applications for advanced use cases

Protocol Compliance

CrewAI's A2A integration provides full protocol compliance:

• Agent Cards: Automatic generation of agent capability descriptions
• Task Execution: Asynchronous task processing with event queues
• Artifact Management: Conversion of crew outputs to A2A artifacts
• Error Handling: A2A-compliant error responses and status codes

Use Cases

Remote Agent Networks

Expose CrewAI crews as part of larger agent networks:

# Multi-agent system with specialized crews
research_crew = create_research_crew()
analysis_crew = create_analysis_crew()
writing_crew = create_writing_crew()

# Expose each as A2A agents on different ports
start_a2a_server(CrewAgentExecutor(research_crew), port=10001)
start_a2a_server(CrewAgentExecutor(analysis_crew), port=10002)
start_a2a_server(CrewAgentExecutor(writing_crew), port=10003)

Cross-Platform Integration

Enable CrewAI crews to work with other agent frameworks:

# CrewAI crew accessible to other A2A-compatible systems
executor = CrewAgentExecutor(crew)
start_a2a_server(executor, host="0.0.0.0", port=10001)

# Other systems can now invoke this crew remotely

Advanced Configuration

Custom Agent Cards

from a2a.types import AgentCard, AgentCapabilities, AgentSkill

# Custom agent card for specialized capabilities
agent_card = AgentCard(
    name="Specialized Research Crew",
    description="Advanced research and analysis capabilities",
    version="2.0.0",
    capabilities=AgentCapabilities(
        streaming=True,
        pushNotifications=False
    ),
    skills=[
        AgentSkill(
            id="research",
            name="Research Analysis",
            description="Comprehensive research and analysis",
            tags=["research", "analysis", "data"]
        )
    ]
)

Error Handling

The A2A integration includes comprehensive error handling:

• Validation Errors: Input validation with clear error messages
• Execution Errors: Crew execution errors converted to A2A artifacts
• Cancellation: Proper task cancellation support
• Timeouts: Configurable timeout handling

Best Practices

1. Resource Management: Monitor crew resource usage in server environments
2. Error Handling: Implement proper error handling in crew tasks
3. Security: Use appropriate authentication and authorization
4. Monitoring: Monitor A2A server performance and health
5. Scaling: Consider load balancing for high-traffic scenarios

Limitations

• Optional Dependency: A2A support requires additional dependencies
• Transport Support: Currently supports Starlette transport only
• Synchronous Crews: Crews execute synchronously within async A2A context

Examples

See the examples/a2a_integration_example.py file for a complete working example of A2A integration with CrewAI.