Google A2A Agent
by system32miro
This repository provides an example implementation of Google's Agent-to-Agent (A2A) communication protocol. It showcases how AI agents can communicate with each other through a standardized API.
Last updated: N/A
What is Google A2A Agent?
This is a simple Agent-to-Agent (A2A) communication example based on Google's A2A protocol, demonstrating how AI agents can interact using a standardized API. It includes a Flask-based server acting as an AI agent and a client for interacting with the server.
How to use Google A2A Agent?
To use this example, clone the repository, create a virtual environment, install dependencies, set up API keys in a .env file, and run the server and client scripts separately. The client will then send a task to the server and print the agent's response.
Key features of Google A2A Agent
Implements Google's A2A protocol
Flask-based server with Agent Card and task handling
Client for interacting with the server
Integration with OpenAI's GPT-4o-mini
Integration with Brave Search via MCP
Use cases of Google A2A Agent
Demonstrating A2A communication
Building AI agents that can collaborate
Experimenting with standardized agent APIs
Integrating AI models with external tools
Creating conversational AI applications
FAQ from Google A2A Agent
What is the Agent Card?
What is the Agent Card?
The Agent Card is a standard JSON document describing an agent's identity, capabilities, and API endpoints.
What is the Task API?
What is the Task API?
The Task API provides endpoints for exchanging tasks and messages between agents.
What is MCP?
What is MCP?
MCP (Model Context Protocol) standardizes how AI models interact with external tools/data sources.
What API keys do I need?
What API keys do I need?
You need an OpenAI API key and a Brave API key.
Where can I find the official Google A2A protocol documentation?
Where can I find the official Google A2A protocol documentation?
Refer to the official Google A2A protocol documentation (link if available).