agent-framework/python/samples/04-hosting/a2a/README.md

A2A Agent Examples

This sample demonstrates how to host and consume agents using the A2A (Agent2Agent) protocol with the agent_framework package. There are three runnable entry points:

Run this file	To...
a2a_server.py	Host an Agent Framework agent as an A2A-compliant server.
agent_with_a2a.py	Connect to an A2A server and send requests (non-streaming and streaming).
a2a_agent_as_function_tools.py	Convert A2A agent skills into function tools for a host agent.

The remaining files are supporting modules used by the server:

File	Description
agent_framework_to_a2a.py	Exposes an agent_framework agent as an A2A-compliant server. Demonstrates how to wrap an agent_framework agent and expose it as an A2A service that other A2A clients can discover and communicate with.
agent_definitions.py	Agent and AgentCard factory definitions for invoice, policy, and logistics agents.
agent_executor.py	Bridges the a2a-sdk AgentExecutor interface to Agent Framework agents.
invoice_data.py	Mock invoice data and tool functions for the invoice agent.
a2a_server.http	REST Client requests for testing the server directly from VS Code.

Environment Variables

Make sure to set the following environment variables before running the examples:

Required (Server)

• FOUNDRY_PROJECT_ENDPOINT — Your Azure AI Foundry project endpoint
• FOUNDRY_MODEL — Model deployment name (e.g. gpt-4o)

Required (Client)

• A2A_AGENT_HOST — URL of the A2A server (e.g. http://localhost:5001/)

Required (Function Tools Sample)

• A2A_AGENT_HOST — URL of the A2A server (e.g. http://localhost:5000/)
• FOUNDRY_PROJECT_ENDPOINT — Your Azure AI Foundry project endpoint
• FOUNDRY_MODEL — Model deployment name (e.g. gpt-4o)

Quick Start

All commands below should be run from this directory:

cd python/samples/04-hosting/a2a

0. Install Dependencies

Copy .env.example to .env and fill in your values:

copy .env.example .env

Option A — pip (standard):

python -m venv .venv
.venv\Scripts\Activate.ps1      # Windows
# source .venv/bin/activate     # macOS / Linux
pip install -r requirements.txt

Option B — uv:

uv run python a2a_server.py --agent-type policy

1. Start the A2A Server

Note (Option A — pip users): Replace uv run python with python in all uv run commands below (e.g. python a2a_server.py ...). uv is not required once the virtual environment is activated.

Pick an agent type and start the server (each in its own terminal):

uv run python a2a_server.py --agent-type invoice --port 5000
uv run python a2a_server.py --agent-type policy --port 5001
uv run python a2a_server.py --agent-type logistics --port 5002

You can run one agent or all three — each listens on its own port.

2. Run the A2A Client

In a separate terminal (from the same directory), point the client at a running server:

$env:A2A_AGENT_HOST = "http://localhost:5001/"
uv run python agent_with_a2a.py

# A2A server exposing an agent_framework agent
uv run python agent_framework_to_a2a.py

3. Run the Function Tools Sample

This sample resolves the remote agent's skills and registers each one as a function tool on a host Foundry-backed agent. The host agent then autonomously selects the right skill to handle the user's request.

$env:A2A_AGENT_HOST = "http://localhost:5000/"
uv run python a2a_agent_as_function_tools.py