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a2aproject/A2A

Built by a2aproject • 22,874 stars

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What is a2aproject/A2A?

Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.

How to use a2aproject/A2A?

1. Install a compatible MCP client (like Claude Desktop). 2. Open your configuration settings. 3. Add a2aproject/A2A using the following command: npx @modelcontextprotocol/a2aproject-a2a 4. Restart the client and verify the new tools are active.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/a2aproject-a2a --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/a2aproject-a2a

Key Features

Native MCP Protocol Support
Real-time Tool Activation & Execution
Verified High-performance Implementation
Secure Resource & Context Handling

Optimized Use Cases

Extending AI models with custom local capabilities
Automating system workflows via natural language
Connecting external data sources to LLM context windows

a2aproject/A2A FAQ

Q

Is a2aproject/A2A safe?

Yes, a2aproject/A2A follows the standardized Model Context Protocol security patterns and only executes tools with explicit user-granted permissions.

Q

Is a2aproject/A2A up to date?

a2aproject/A2A is currently active in the registry with 22,874 stars on GitHub, indicating its reliability and community support.

Q

Are there any limits for a2aproject/A2A?

Usage limits depend on the specific implementation of the MCP server and your system resources. Refer to the official documentation below for technical details.

Official Documentation

View on GitHub

Agent2Agent (A2A) Protocol

PyPI - Version Apache License <a href="https://codewiki.google/github.com/a2aproject/a2a"> <img src="https://www.gstatic.com/_/boq-sdlc-agents-ui/_/r/Mvosg4klCA4.svg" alt="Ask Code Wiki" height="20"> </a>

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An open protocol enabling communication and interoperability between opaque agentic applications.

The Agent2Agent (A2A) protocol addresses a critical challenge in the AI landscape: enabling gen AI agents, built on diverse frameworks by different companies running on separate servers, to communicate and collaborate effectively - as agents, not just as tools. A2A aims to provide a common language for agents, fostering a more interconnected, powerful, and innovative AI ecosystem.

With A2A, agents can:

  • Discover each other's capabilities.
  • Negotiate interaction modalities (text, forms, media).
  • Securely collaborate on long-running tasks.
  • Operate without exposing their internal state, memory, or tools.

DeepLearning.AI Course

A2A DeepLearning.AI

Join this short course on A2A: The Agent2Agent Protocol, built in partnership with Google Cloud and IBM Research, and taught by Holt Skinner, Ivan Nardini, and Sandi Besen.

What you'll learn:

  • Make agents A2A-compliant: Expose agents built with frameworks like Google ADK, LangGraph, or BeeAI as A2A servers.
  • Connect agents: Create A2A clients from scratch or using integrations to connect to A2A-compliant agents.
  • Orchestrate workflows: Build sequential and hierarchical workflows of A2A-compliant agents.
  • Multi-agent systems: Build a healthcare multi-agent system using different frameworks and see how A2A enables collaboration.
  • A2A and MCP: Learn how A2A complements MCP by enabling agents to collaborate with each other.

Why A2A?

As AI agents become more prevalent, their ability to interoperate is crucial for building complex, multi-functional applications. A2A aims to:

  • Break Down Silos: Connect agents across different ecosystems.
  • Enable Complex Collaboration: Allow specialized agents to work together on tasks that a single agent cannot handle alone.
  • Promote Open Standards: Foster a community-driven approach to agent communication, encouraging innovation and broad adoption.
  • Preserve Opacity: Allow agents to collaborate without needing to share internal memory, proprietary logic, or specific tool implementations, enhancing security and protecting intellectual property.

Key Features

  • Standardized Communication: JSON-RPC 2.0 over HTTP(S).
  • Agent Discovery: Via "Agent Cards" detailing capabilities and connection info.
  • Flexible Interaction: Supports synchronous request/response, streaming (SSE), and asynchronous push notifications.
  • Rich Data Exchange: Handles text, files, and structured JSON data.
  • Enterprise-Ready: Designed with security, authentication, and observability in mind.

Getting Started

Contributing

We welcome community contributions to enhance and evolve the A2A protocol!

  • Questions & Discussions: Join our GitHub Discussions.
  • Issues & Feedback: Report issues or suggest improvements via GitHub Issues.
  • Contribution Guide: See our CONTRIBUTING.md for details on how to contribute.
  • Private Feedback: Use this Google Form.
  • Partner Program: Google Cloud customers can join our partner program via this form.

What's next

Protocol Enhancements

  • Agent Discovery:
    • Formalize inclusion of authorization schemes and optional credentials directly within the AgentCard.
  • Agent Collaboration:
    • Investigate a QuerySkill() method for dynamically checking unsupported or unanticipated skills.
  • Task Lifecycle & UX:
    • Support for dynamic UX negotiation within a task (e.g., agent adding audio/video mid-conversation).
  • Client Methods & Transport:
    • Explore extending support to client-initiated methods (beyond task management).
    • Improvements to streaming reliability and push notification mechanisms.

About

The A2A Protocol is an open source project under the Linux Foundation, contributed by Google. It is licensed under the Apache License 2.0 and is open to contributions from the community.

Global Ranking

8.5
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

{ "mcpServers": { "a2aproject-a2a": { "command": "npx", "args": ["a2aproject-a2a"] } } }