Multi-Agent System with Microsoft Agent Framework on AKS or ACA

A production-ready multi-agent orchestration system built with Microsoft Agent Framework (MAF), Agent-to-Agent (A2A) Protocol, Model Context Protocol (MCP), and Azure Kubernetes Service (AKS) or Azure Container Apps (ACA).

🏗️ Architecture

                        ┌─────────────────────┐
                        │   Streamlit UI      │
                        │   (LoadBalancer)    │
                        └──────────┬──────────┘
                                   │
                                   │ HTTP
                                   │
                        ┌──────────▼──────────┐
                        │   Orchestrator      │
                        │   (LoadBalancer)    │
                        │   AKS (2 replicas)  │
                        └──────────┬──────────┘
                                   │
                    ┌──────────────┼──────────────┐
                    │              │              │
         A2A Simple │   A2A Simple │   A2A SDK    │ A2A SDK
                    │              │   (JSON-RPC) │ (JSON-RPC)
         ┌──────────▼─────┐ ┌─────▼──────┐ ┌────▼─────┐ ┌────▼─────┐
         │ Travel Agent   │ │ Streamlit  │ │ Burger   │ │ Pizza    │
         │ (AKS or ACA)   │ │(AKS or ACA)│ │ Agent    │ │ Agent    │
         │ LoadBalancer   │ │            │ │ (GCP)    │ │ (GCP)    │
         └────────┬───────┘ └────────────┘ └──────────┘ └──────────┘
                  │
          MCP StreamableHTTP
                  │
         ┌────────┴────────┐
         │                 │
  ┌──────▼───────┐  ┌─────▼────────┐
  │ Currency MCP │  │ Activity MCP │
  │ (AKS or ACA) │  │ (AKS or ACA) │
  │ Port 8001    │  │ Port 8002    │
  └──────────────┘  └──────────────┘

Components

• Streamlit UI (AKS or ACA): User interface for multi-agent interaction
• Orchestrator (AKS or ACA): Routes tasks to appropriate agents using A2A protocol
• Travel Agent (AKS or ACA): Handles travel planning, currency conversion, restaurant recommendations
• Burger Agent (GCP Cloud Run): Processes burger orders - Source Code
• Pizza Agent (GCP Cloud Run): Processes pizza orders - Source Code
• Currency MCP (AKS or ACA): Real-time exchange rates via Frankfurter API
• Activity MCP (AKS or ACA): Travel itinerary and activity planning

Protocol Support

The orchestrator implements dual protocol support:

1. A2A Simple Format (Travel Agent):

   {"task": "...", "user_id": "..."}
   

2. A2A SDK JSON-RPC Format (GCP Agents - Burger & Pizza):

   {
     "id": "msg-123",
     "params": {
       "message": {
         "role": "user",
         "parts": [{"type": "text", "text": "..."}]
       }
     }
   }
   

📁 Project Structure

MultiAgent-AKS-MAF/
├── agents/                      # MAF-based agents
│   ├── orchestrator/           # Main orchestrator (A2A + Service Bus)
│   │   ├── main.py
│   │   ├── requirements.txt
│   │   └── Dockerfile
│   │
│   ├── travel_agent/           # Travel planning agent
│   │   ├── main.py
│   │   ├── requirements.txt
│   │   ├── Dockerfile
│   │   └── .well-known/
│   │       └── agent.json      # AgentCard for A2A discovery
│   │
│   └── external_agent/         # External A2A agent integration
│       ├── README.md          # Integration guide
│       └── .well-known/
│           └── agent.json     # AgentCard template
│
├── mcp_servers/                # Model Context Protocol servers
│   ├── currency_mcp/          # Currency exchange tools
│   │   ├── server.py
│   │   ├── requirements.txt
│   │   └── Dockerfile
│   │
│   └── activity_mcp/          # Activity planning tools
│       ├── server.py
│       ├── requirements.txt
│       └── Dockerfile
│
├── infrastructure/             # Azure infrastructure (Bicep)
│   └── bicep/
│       ├── main-rg.bicep      # Main resource group deployment
│       └── modules/           # Individual Azure resources
│
├── k8s/                       # Kubernetes manifests
│   ├── orchestrator-deployment.yaml
│   ├── travel-agent-deployment.yaml
│   ├── currency-mcp-deployment.yaml
│   └── activity-mcp-deployment.yaml
│
├── scripts/                   # Deployment scripts
│   ├── deploy-infrastructure.sh
│   ├── build-and-push.sh
│   └── deploy-to-aks.sh
│
└── _archived/                 # Old code (for reference)

🚀 Key Technologies

• Microsoft Agent Framework (MAF): Agent orchestration and communication
• Azure AI Foundry: GPT-4o, GPT-4o-mini models
• A2A Protocol: Agent-to-Agent communication standard (Simple + SDK formats)
• MCP (Model Context Protocol): Tool/plugin architecture
• Azure Service Bus: Message queue for external communication
• Azure Kubernetes Service (AKS) or Azure Container Apps (ACA): Container orchestration
• Google Cloud Run: Serverless container hosting (for food ordering agents)
• Azure Managed Identity: Secure authentication

✨ Features

Orchestrator

• ✅ Discovers agents via A2A AgentCard resolution
• ✅ Dual Protocol Support: A2A Simple + A2A SDK (JSON-RPC 2.0)
• ✅ Multi-cloud agent integration (AKS + GCP Cloud Run)
• ✅ Routes tasks based on keywords and agent capabilities
• ✅ Supports external A2A-compliant agents

Travel Agent (AKS or ACA)

• ✅ Built with ChatAgent from MAF
• ✅ Uses MCP tools for currency and activity planning
• ✅ Exposes AgentCard at /.well-known/agent.json
• ✅ Supports Azure Managed Identity
• ✅ Real-time currency conversion (30+ currencies)
• ✅ Restaurant recommendations
• ✅ Multi-day itinerary planning

Food Ordering Agents (GCP Cloud Run)

• ✅ Burger Agent: Processes burger orders using A2A SDK format
• ✅ Pizza Agent: Processes pizza orders using A2A SDK format
• ✅ Source: Purchasing Concierge A2A Codelab
• ✅ Deployed on Google Cloud Run
• ✅ Integrated via A2A JSON-RPC 2.0 protocol

Streamlit Web UI (AKS or ACA)

• ✅ User-friendly interface for multi-agent interaction
• ✅ Quick test buttons for common tasks
• ✅ Contextual follow-up questions
• ✅ Clean response formatting with expandable raw JSON
• ✅ Support for all agent types (travel, burger, pizza)

MCP Servers (AKS or ACA)

• ✅ Currency MCP: Exchange rates via Frankfurter API
• ✅ Activity MCP: Trip planning, recommendations

🔧 Prerequisites

• Azure subscription
• Azure CLI (az)
• kubectl
• Docker
• Python 3.11+

📦 Quick Start

1. Deploy Infrastructure

# Login to Azure
az login

# Deploy infrastructure
./scripts/deploy-infrastructure.sh

This creates:

• Azure OpenAI (with gpt-4o, gpt-4o-mini, gpt-35-turbo)
• Azure Service Bus
• Azure Key Vault
• AKS Cluster with Workload Identity
• Azure Container Registry

2. Deploy to AKS

Option A: GitHub Actions (Recommended) 🚀

See GitHub Actions Deployment Guide for automated CI/CD setup.

Quick setup:

# Create service principal with federated credentials
# See .github/DEPLOYMENT_QUICKSTART.md for complete script

# Add GitHub Secrets (Settings → Secrets):
# - AZURE_CLIENT_ID
# - AZURE_TENANT_ID  
# - AZURE_SUBSCRIPTION_ID

# Push to main branch → auto-deploys!
git push origin main

Option B: Manual Deployment

# Build and deploy all services
./scripts/deploy-to-aks.sh

This will:

• Build Docker images for all 3 services
• Push to Azure Container Registry
• Deploy to AKS with Workload Identity
• Configure session affinity for MCP servers
• Wait for pods and get external IP

🧪 Testing

Test the Complete System

Via Streamlit UI (Recommended):

Open browser: http://<STREAMLIT_UI_IP>

Quick Test Buttons:
- 🍔 Order Burgers → Routes to Burger Agent (GCP)
- 🍕 Order Pizza → Routes to Pizza Agent (GCP)
- 💱 Convert Currency → Routes to Travel Agent (AKS)
- ✈️ Plan Trip → Routes to Travel Agent (AKS)

Test Orchestrator Directly

Get the orchestrator IP: kubectl get svc orchestrator-service -n multiagent

# Travel Agent - Currency conversion
curl -X POST http://<ORCHESTRATOR_IP>/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Convert 100 USD to EUR", "user_id": "test"}'

# Travel Agent - Trip planning
curl -X POST http://<ORCHESTRATOR_IP>/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Plan a 3-day trip to Paris", "user_id": "test"}'

# Burger Agent (GCP)
curl -X POST http://<ORCHESTRATOR_IP>/task \
  -H "Content-Type: application/json" \
  -d '{"task": "I want 2 classic cheeseburgers", "user_id": "test"}'

# Pizza Agent (GCP)
curl -X POST http://<ORCHESTRATOR_IP>/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Order 1 pepperoni pizza", "user_id": "test"}'

# Check discovered agents
curl http://<ORCHESTRATOR_IP>/agents

Test Locally

# Start Currency MCP
cd mcp_servers/currency_mcp
python server.py

# Test in another terminal
curl http://localhost:8001/health

Test Travel Agent

cd agents/travel_agent
python main.py

# Query the agent
curl -X POST http://localhost:8080/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Convert 500 USD to EUR", "user_id": "local-test"}'

Test Orchestrator Agent Discovery

cd agents/orchestrator
# Set environment variable with agent endpoints
export AGENT_ENDPOINTS="http://travel-agent-service,https://burger-agent-286879789617.us-central1.run.app,https://pizza-agent-286879789617.us-central1.run.app"
python main.py

# Check discovered agents
curl http://localhost:8000/agents

🔐 Security

• Managed Identity: All Azure resources use managed identities
• RBAC: Service Bus and Key Vault use role-based access
• No API Keys: Credentials stored in Key Vault
• Network Isolation: Private endpoints for Azure services

📊 Monitoring

• Application Insights: Telemetry and logging
• Azure Monitor: Infrastructure metrics
• Service Bus Metrics: Message queue monitoring

🛠️ Development

Adding a New Agent

1. Create agent directory: agents/my_agent/
2. Implement using MAF ChatAgent
3. Create agent.json AgentCard
4. Build Docker image
5. Create K8s deployment manifest

Adding MCP Tools

1. Create MCP server: mcp_servers/my_tools/
2. Implement tools following MCP spec
3. Register with Travel Agent
4. Deploy to AKS

📚 Resources

• Microsoft Agent Framework
• A2A Protocol
• Model Context Protocol
• Azure AI Foundry
• GCP Food Ordering Agents (Burger & Pizza)

🎯 Live Demo

Get the service IPs using:

kubectl get svc -n multiagent

Services:

• Streamlit UI: streamlit-service (LoadBalancer)
• Orchestrator: orchestrator-service (LoadBalancer)
• Travel Agent: travel-agent-service (LoadBalancer)
• Burger Agent (GCP): External Cloud Run service
• Pizza Agent (GCP): External Cloud Run service

📝 License

MIT License - see LICENSE file for details

🤝 Contributing

Contributions welcome! Please read CONTRIBUTING.md first.

🙏 Acknowledgments

• Microsoft Agent Framework Team - Multi-agent orchestration framework
• A2A Protocol Contributors - Agent-to-Agent communication standard
• Model Context Protocol - Tool integration standard
• Frankfurter API - Free currency exchange data
• alphinside/purchasing-concierge-intro-a2a-codelab-starter - GCP food ordering agents

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Built with ❤️ using Microsoft Agent Framework + A2A Protocol