Back to rankings

a2aproject/A2A

Shella2a-protocol.org

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

a2aa2a-mcpa2a-protocola2a-serveragentsgenerative-ailinux-foundation
Star Growth
Stars
24.9k
Forks
2.5k
Weekly Growth
Issues
166
18k20k22k24k
Apr 2025Sep 2025Feb 2026Jul 2026
README

Agent2Agent (A2A) Protocol

PyPI - Version Apache License Ask Code Wiki

Agent2Agent Protocol Logo

Agent2Agent (A2A) Protocol

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.

Related repositories
diegosouzapw/OmniRoute

Never stop coding. Free MIT AI gateway: one endpoint, 268+ providers (50+ free), 500+ models — Kimi, Claude, GPT, OpenAI, Gemini, GLM, DeepSeek, MiniMax. Works with Claude Code, Codex, Cursor, OpenCode, Cline & Copilot. Quota-aware auto-fallback, RTK+Caveman compression saves 15-95% tokens, MCP/A2A, Desktop/PWA. Built by 500+ contributors

TypeScriptnpmMIT Licensea2aai-agents
omniroute.online
23.8k3.2k
EvoMap/evolver

The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai

JavaScriptnpmGNU General Public License v3.0a2aagent-evolution
evomap.ai
8.9k822
google/adk-go

An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

GoGo ModulesApache License 2.0a2aagents
google.github.io/adk-docs/
8.5k811
GetBindu/Bindu

Bindu: The identity, communication, and payments layer for AI agents.

PythonPyPIOtheragent-communicationautonomous-agents
docs.getbindu.com
7.8k422
SolaceLabs/solace-agent-mesh

An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.

PythonPyPIApache License 2.0agentframeworkagents
solacelabs.github.io/solace-agent-mesh/
5k271
ag2ai/ag2

AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3x

PythonPyPIApache License 2.0a2aagent-framework
ag2.ai
4.8k678
panaversity/learn-agentic-ai

Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.

Jupyter NotebookMIT Licenseagentic-ailangmem
4.3k996
archestra-ai/archestra

Enterprise AI Platform with guardrails, MCP registry, gateway & orchestrator

TypeScriptnpmOthera2aacp
archestra.ai
4k1.1k
evalstate/fast-agent

Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support

PythonPyPIApache License 2.0agentagent-framework
fast-agent.ai
3.9k418
a2aproject/a2a-python

Official Python SDK for the Agent2Agent (A2A) Protocol

PythonPyPIApache License 2.0agentsgenerative-ai
a2a-protocol.org/latest/sdk/python/api/
2k459
a2aproject/a2a-samples

Samples using the Agent2Agent (A2A) Protocol

Jupyter NotebookApache License 2.0a2aa2a-client
a2a-protocol.org
1.7k713
trpc-group/trpc-agent-go

A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, evaluation, and observability.

GoGo ModulesApache License 2.0a2aagent
trpc-group.github.io/trpc-agent-go/
1.6k253