agent-framework/dotnet/samples/05-end-to-end/A2AClientServer

A2A Client and Server samples

Warning

The A2A protocol is still under development and changing fast. We will try to keep these samples updated as the protocol evolves.

These samples are built with official A2A C# SDK and demonstrates:

1. Creating an A2A Server which makes an agent available via the A2A protocol.
2. Creating an A2A Client with a command line interface which invokes agents using the A2A protocol.

The demonstration has two components:

1. A2AServer - You will run three instances of the server to correspond to three A2A servers each providing a single Agent i.e., the Invoice, Policy and Logistics agents.
2. A2AClient - This represents a client application which will connect to the remote A2A servers using the A2A protocol so that it can use those agents when answering questions you will ask.

Configuring Environment Variables

The samples can be configured to use chat completion agents or Azure AI agents.

Configuring for use with Chat Completion Agents

Provide your OpenAI API key via an environment variable

$env:OPENAI_API_KEY="<Your OpenAI API Key>"

Use the following commands to run each A2A server:

Execute the following command to build the sample:

cd A2AServer
dotnet build

dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentType "invoice" --no-build

dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentType "policy" --no-build

dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentType "logistics" --no-build

Configuring for use with Azure AI Agents

You must create the agents in a Microsoft Foundry project and then provide the project endpoint and agent IDs. The instructions for each agent are as follows:

• Invoice Agent

  You specialize in handling queries related to invoices.
  

• Policy Agent

  You specialize in handling queries related to policies and customer communications.
  
  Always reply with exactly this text:
  
  Policy: Short Shipment Dispute Handling Policy V2.1
  
  Summary: "For short shipments reported by customers, first verify internal shipment records
  (SAP) and physical logistics scan data (BigQuery). If discrepancy is confirmed and logistics data
  shows fewer items packed than invoiced, issue a credit for the missing items. Document the
  resolution in SAP CRM and notify the customer via email within 2 business days, referencing the
  original invoice and the credit memo number. Use the 'Formal Credit Notification' email
  template."
  

• Logistics Agent

  You specialize in handling queries related to logistics.
  
  Always reply with exactly:
  
      Shipment number: SHPMT-SAP-001
      Item: TSHIRT-RED-L
      Quantity: 900"
  

$env:AZURE_AI_PROJECT_ENDPOINT="https://ai-foundry-your-project.services.ai.azure.com/api/projects/ai-proj-ga-your-project" # Replace with your Foundry Project endpoint

Use the following commands to run each A2A server

dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentName "<Invoice Agent Name>" --agentType "invoice" --no-build

dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentName "<Policy Agent Name>" --agentType "policy" --no-build

dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentName "<Logistics Agent Name>" --agentType "logistics" --no-build

Testing the Agents using the Rest Client

This sample contains a .http file which can be used to test the agent.

1. In Visual Studio open ./A2AServer/A2AServer.http
2. There are two sent requests for each agent, e.g., for the invoice agent:
   1. Query agent card for the invoice agent GET {{hostInvoice}}/.well-known/agent-card.json
   2. Send a message to the invoice agent

      POST {{hostInvoice}}
      Content-Type: application/json
      
      {
          "id": "1",
          "jsonrpc": "2.0",
          "method": "message/send",
          "params": {
              "id": "12345",
              "message": {
                  "kind": "message",
                  "role": "user",
                  "messageId": "msg_1",
                  "parts": [
                      {
                          "kind": "text",
                          "text": "Show me all invoices for Contoso?"
                      }
                  ]
              }
          }
      }
      

Sample output from the request to display the agent card:

Sample output from the request to send a message to the agent via A2A protocol:

Testing the Agents using the A2A Inspector

The A2A Inspector is a web-based tool designed to help developers inspect, debug, and validate servers that implement the Google A2A (Agent2Agent) protocol. It provides a user-friendly interface to interact with an A2A agent, view communication, and ensure specification compliance.

For more information go here.

Running the inspector with Docker is the easiest way to get started.

1. Navigate to the A2A Inspector in your browser: http://127.0.0.1:8080/
2. Enter the URL of the Agent you are running e.g., http://host.docker.internal:5000
3. Connect to the agent and the agent card will be displayed and validated.
4. Type a message and send it to the agent using A2A protocol.
   1. The response will be validated automatically and then displayed in the UI.
   2. You can select the response to view the raw json.

Agent card after connecting to an agent using the A2A protocol:

Sample response after sending a message to the agent via A2A protocol:

Raw JSON response from an A2A agent:

Configuring Agents for the A2A Client

The A2A client will connect to remote agents using the A2A protocol.

By default the client will connect to the invoice, policy and logistics agents provided by the sample A2A Server.

These are available at the following URL's:

• Invoice Agent: http://localhost:5000/
• Policy Agent: http://localhost:5001/
• Logistics Agent: http://localhost:5002/

If you want to change which agents are using then set the agents url as a space delimited string as follows:

$env:A2A_AGENT_URLS="http://localhost:5000/;http://localhost:5001/;http://localhost:5002/"

Run the Sample

To run the sample, follow these steps:

1. Run the A2A server's using the commands shown earlier
2. Run the A2A client:

   cd A2AClient
   dotnet run
   

3. Enter your request e.g. "Customer is disputing transaction TICKET-XYZ987 as they claim the received fewer t-shirts than ordered."
4. The host client agent will call the remote agents, these calls will be displayed as console output. The final answer will use information from the remote agents. The sample below includes all three agents but in your case you may only see the policy and invoice agent.

Sample output from the A2A client:

A2AClient> dotnet run
info: HostClientAgent[0]
      Initializing Agent Framework agent with model: gpt-4o-mini

User (:q or quit to exit): Customer is disputing transaction TICKET-XYZ987 as they claim the received fewer t-shirts than ordered.

Agent:

Agent:

Agent: The transaction details for **TICKET-XYZ987** are as follows:

- **Invoice ID:** INV789
- **Company Name:** Contoso
- **Invoice Date:** September 4, 2025
- **Products:**
  - **T-Shirts:** 150 units at $10.00 each
  - **Hats:** 200 units at $15.00 each
  - **Glasses:** 300 units at $5.00 each

To proceed with the dispute regarding the quantity of t-shirts delivered, please specify the exact quantity issue � how many t-shirts were actually received compared to the ordered amount.

### Customer Service Policy for Handling Disputes
**Short Shipment Dispute Handling Policy V2.1**
- **Summary:** For short shipments reported by customers, first verify internal shipment records and physical logistics scan data. If a discrepancy is confirmed and the logistics data shows fewer items were packed than invoiced, a credit for the missing items will be issued.
- **Follow-up Actions:** Document the resolution in the SAP CRM and notify the customer via email within 2 business days, referencing the original invoice and the credit memo number, using the 'Formal Credit Notification' email template.

Please provide me with the information regarding the specific quantity issue so I can assist you further.