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a2aproject/A2A

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What is a2aproject/A2A?

A high-performance MCP server implementation for a2aproject/A2A that bridges the gap between the Model Context Protocol and external services. It allows Large Language Models to interact with your data and tools with low latency and native support.

How to use a2aproject/A2A?

1. Ensure you have an MCP-compatible client (like Claude Desktop) installed. 2. Configure your server with: npx @modelcontextprotocol/a2aproject/A2A 3. Restart your client and verify the new tools are available in the system catalog.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/a2aproject-a2a --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/a2aproject-a2a

Key Features

Native MCP Protocol Support
High-performance Data Streaming
Type-safe Tool Definitions
Seamless Environment Integration

Optimized Use Cases

Connecting external databases to AI workflows
Automating workflow tasks via natural language
Augmenting developer productivity with specialized tools

a2aproject/A2A FAQ

Q

What is an MCP server?

MCP is an open standard that enables developers to build secure, two-way integrations between AI models and local or remote data sources.

Q

Is this server ready for production?

Yes, this server follows standard MCP security patterns and tool-restricted access.

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!

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

7.5
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

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