This repository curates resources for the Google Agent2Agent (A2A) Protocol, an open standard enabling secure and collaborative communication between diverse AI agents. It targets developers and researchers building interoperable AI systems, offering a centralized hub for implementations, tools, and documentation to facilitate cross-application automation.

How It Works

A2A operates on existing standards like HTTP and JSON-RPC, with an asynchronous, modality-agnostic design. Agents expose capabilities via an "Agent Card" (JSON), allowing clients to discover and invoke tasks. Communication involves task requests with "Parts" (data payloads) and responses containing "Artifacts." Long-running tasks can utilize Server-Sent Events (SSE) for status updates, promoting enterprise readiness through built-in security and monitoring.

Quick Start & Requirements

• Install/Run: Clone the official google/A2A repository and follow instructions in the /samples directory for CLI clients and sample agents (e.g., LangGraph, Genkit).
• Prerequisites: Python, JavaScript/TypeScript environments. Specific agent framework integrations may have additional dependencies.
• Resources: Official documentation, demo videos, and a multi-agent web app demo are available.

Highlighted Details

• Protocol Specification: Detailed JSON schemas and core concepts for Agent Cards, Tasks, Messages, Parts, and Artifacts.
• Official Samples: Demonstrations of A2A client/server communication in Python and JS/TS, including CLI clients and orchestrator agents.
• Framework Integrations: Examples of integrating A2A with popular agent frameworks like LangGraph, CrewAI, Google ADK, and Genkit.
• Community Implementations: A growing list of SDKs and libraries in Go, Rust, Python, C#/.NET, and Java.

Maintenance & Community

• Official Resources: google/A2A GitHub repository for issues and discussions.
• Community Driven: This list is community-curated, encouraging contributions via Issues or Pull Requests.

Licensing & Compatibility

• License: Not explicitly stated in the README. The google/A2A repository should be checked for licensing details.
• Compatibility: Designed for interoperability between different AI agents and frameworks.

Limitations & Caveats

The A2A ecosystem is described as "still pretty new," indicating potential for evolving standards and a developing community resource base. Some community implementations are marked as "Work in Progress."