awesome-a2a

One-Minute Overview#

Agent2Agent (A2A) is an open protocol from Google and partners that enables different AI agents (from various vendors/frameworks) to communicate securely and collaborate on tasks. It breaks down silos between isolated agent systems, enabling more complex cross-application automation.

Core Value: Provides a unified standard for AI agents to interoperate across frameworks, building an ecosystem for composite AI applications.

Quick Start#

Installation Difficulty: Low - Offers official samples and SDKs in multiple languages, from simple "Hello World" to complete reference implementations

# Clone the official samples repository to get started
git clone https://github.com/a2aproject/a2a-samples.git

Is this suitable for my scenario?

• ✅ Multi-agent collaboration systems: Need different AI frameworks to work together
• ✅ Enterprise AI applications: Require security, authentication, and monitoring features
• ❌ Simple single-task AI: Applications that don't need to interact with other agents

Core Capabilities#

1. Agent Discovery and Registration - Solving the problem of finding collaboration partners#

• Agents publish their capabilities, endpoints, and authentication requirements through an Agent Card Actual Value: Applications automatically discover needed services without hardcoded connection information

2. Secure Communication - Solving the problem of trusted exchange between different systems#

• Based on existing standards (HTTP, JSON-RPC, SSE) with enterprise-grade authentication and security Actual Value: Secure deployment of AI agents in enterprise environments while protecting data and privacy

3. Asynchronous Task Processing - Solving the problem of long-running tasks#

• Supports long task processing with human-in-the-loop, updating status via Server-Sent Events or push notifications Actual Value: Handle complex AI tasks like document generation, data analysis that take longer time

4. Multi-Modality Support - Solving the problem of diverse data exchange#

• Supports various data types including text, files, forms, streams, etc. Actual Value: Agents can exchange and process different types of data like images, documents

5. Modality-Agnostic Execution - Solving the problem of internal logic exposure#

• Agents interact without sharing internal logic or tools, maintaining encapsulation Actual Value: Protect business secrets while enabling complementary functional collaboration

Technology Stack and Integration#

Development Languages: Python, TypeScript/JavaScript, Java, .NET, Go, Rust, C# Main Dependencies: HTTP/JSON-RPC 2.0, Server-Sent Events (SSE), OAuth2/JWT authentication Integration Method: SDK / Library / Framework integration

Ecosystem and Extension#

• Plugins/Extensions: Supports integration with multiple frameworks including LangGraph, CrewAI, Semantic Kernel, AG2
• Integration Capabilities: Can be combined with MCP (Model Context Protocol) for richer agent collaboration scenarios

Maintenance Status#

• Development Activity: Actively maintained, driven by Google and multiple tech companies
• Recent Updates: Recent significant updates with continuous improvements to multi-language SDKs
• Community Response: Growing community with implementations in multiple languages and integration with popular AI frameworks

Commercial and Licensing#

License: Apache 2.0

• ✅ Commercial Use: Permitted
• ✅ Modifications: Permitted
• ⚠️ Restrictions: Must include copyright notice and license file

Documentation and Learning Resources#

• Documentation Quality: Comprehensive, including technical specifications, core concepts, and multi-language documentation (Chinese/Japanese/English)
• Official Documentation: https://agent2agent.ren (multi-language) | https://a2aproject.github.io/A2A (English)
• Sample Code: Complete examples in various languages, from simple "Hello World" to complex applications