MCS Proxy A2A Server

💡 The Problem: You're using an agent that speaks A2A. It can talk to cloud-based agents, OpenAI agents, LangGraph agents, homegrown agents, ERP agents... but it can't talk to Copilot Studio (yet). This proxy fixes that.

🎭 The Scenario: A2A Agent Wants to Talk to Copilot Studio

Here's the situation:

A user is working with an agent that has A2A capabilities. That agent can communicate with:

✅ Cloud-based agents (A2A)
✅ OpenAI-based agents (A2A)
✅ LangGraph agents (A2A)
✅ Homegrown agents (A2A)
✅ ERP agents (A2A)
✅ Any other agent speaking A2A
❌ Copilot Studio agents (Direct-to-Engine only)

The Problem: Copilot Studio doesn't speak A2A yet, so it's excluded from the agent ecosystem.

Why it matters: Your Copilot Studio agent has all your company's Power Platform, Dynamics, and Dataverse integrations. It's incredibly valuable, but your A2A agent can't talk to it. That's frustrating.

Without This Proxy

    ┌──────────────────┐
    │      User        │
    └────────┬─────────┘
             │
             ▼
    ┌──────────────────┐
    │   Your Agent     │
    │     (A2A)        │
    └────────┬─────────┘
             │
             │ A2A Protocol (bidirectional)
             │
    ┌────────┼────────┬──────────┬───────────┐
    │        │        │          │           │
    ▼        ▼        ▼          ▼           ▼
┌───────┐ ┌──────┐ ┌────────┐ ┌─────────┐ ┌─────┐
│ Cloud │ │OpenAI│ │LangGraph│ │Homegrown│ │ ERP │
│ Agent │ │Agent │ │ Agent  │ │  Agent  │ │Agent│
│ (A2A) │ │(A2A) │ │  (A2A) │ │  (A2A)  │ │(A2A)│
└───┬───┘ └──┬───┘ └────┬───┘ └────┬────┘ └──┬──┘
    │        │          │          │          │
    └────────┴──────────┴──────────┴──────────┘
                         ▲
                         │
            ✅ Bidirectional A2A communication


     ❌  But it CAN'T talk to Copilot Studio!

                    ┌────────────────┐
                    │ Copilot Studio │
                    │  (Direct-to-   │
                    │   Engine only) │
                    │                │
                    │ + Power        │
                    │ + Dynamics     │
                    │ + Dataverse    │
                    └────────────────┘

With This Proxy 🎉

    ┌──────────────────┐
    │      User        │
    └────────┬─────────┘
             │
             ▼
    ┌──────────────────┐
    │   Your Agent     │
    │     (A2A)        │
    └────────┬─────────┘
             │
             │ A2A Protocol (bidirectional)
             │
    ┌────────┼────────┬──────────┬───────────┬─────────────┐
    │        │        │          │           │             │
    ▼        ▼        ▼          ▼           ▼             ▼
┌───────┐ ┌──────┐ ┌────────┐ ┌─────────┐ ┌─────┐  ┌──────────────┐
│ Cloud │ │OpenAI│ │LangGraph│ │Homegrown│ │ ERP │  │ 🌉 A2A Proxy │
│ Agent │ │Agent │ │ Agent  │ │  Agent  │ │Agent│  │              │
│ (A2A) │ │(A2A) │ │  (A2A) │ │  (A2A)  │ │(A2A)│  │  (Protocol   │
└───┬───┘ └──┬───┘ └────┬───┘ └────┬────┘ └──┬──┘  │  Translator) │
    │        │          │          │          │     └──────┬───────┘
    └────────┴──────────┴──────────┴──────────┘            │
                         ▲                                  │
                         │                                  │ Agent SDK
            ✅ Bidirectional A2A communication               │ (Direct-to-Engine)
                                                            │ + OBO Token Exchange
                                                            │
                                                            ▼
                                                   ┌────────────────┐
                                                   │ Copilot Studio │
                                                   │  + Power       │
                                                   │  + Dynamics    │
                                                   │  + Dataverse   │
                                                   └────────────────┘

✅ Your agent can now communicate bidirectionally with ALL agents including Copilot Studio
✅ Protocol translation happens seamlessly
✅ User identity preserved through OBO token exchange

What This Enables

Universal Agent Communication: Your A2A agent can finally talk to Copilot Studio
Protocol Translation: A2A ↔ Direct-to-Engine conversion handled automatically
User Identity Preservation: OBO flow ensures proper authentication and permissions
No Rewrites: Keep your Copilot Studio investments, just add A2A capability
Future-Proof: When Copilot Studio adds native A2A, swap proxy for direct connection

⚠️ Important Note

This is a thought exercise and educational implementation. It demonstrates:

How A2A protocol integration works
OAuth 2.0 On-Behalf-Of authentication patterns
Protocol translation architectures

For production use, consider:

Microsoft's official A2A support roadmap for Copilot Studio
Enterprise-grade load balancing and state management (Redis)
Comprehensive monitoring and error handling
Security reviews and compliance requirements

This proxy is inspirational - showing what's possible when different AI platforms need to collaborate. Use it to learn, experiment, and prototype your agent orchestration dreams!

🎓 Educational Value

An Agent-to-Agent (A2A) proxy server that forwards requests to Microsoft Copilot Studio agents using OAuth 2.0 On-Behalf-Of (OBO) authentication.

What you'll learn:

A2A protocol implementation and design patterns
OBO authentication flows and token management
Protocol translation and middleware architecture
Multi-agent orchestration concepts

🌟 Overview

This proxy server bridges the gap between standard A2A clients and Microsoft Copilot Studio's Direct-to-Engine API, handling the complexity of token exchange and protocol translation.

What It Does

A2A Client  →  [This Proxy]  →  Copilot Studio Agent
   (JWT)         (Validates)         (Responds)
                 (OBO Exchange)
                 (Translates)

Key Features:

✅ A2A Protocol Support: Standard JSON-RPC 2.0 interface
✅ Azure AD Authentication: JWT token validation with JWKS
✅ OBO Token Exchange: Seamless user identity preservation
✅ Conversation Management: Context-aware multi-turn conversations
✅ Comprehensive Testing: Full test suite with multi-turn and concurrent scenarios

🚀 Quick Start

Prerequisites

Python 3.11+
Azure AD tenant with app registration
Copilot Studio agent (published)
Azure CLI (for testing)

Installation

# Clone or download this project
cd mcs_proxy_a2a_server

# Install dependencies (using uv)
pip install uv
uv sync

# Configure environment
cp .env.example .env
# Edit .env with your Azure AD and Copilot Studio credentials

Configuration

Edit .env:

# Azure AD
AZURE_AD_TENANT_ID=your-tenant-id
AZURE_AD_CLIENT_ID=your-app-id
AZURE_AD_CLIENT_SECRET=your-client-secret
AZURE_AD_AUDIENCE=api://your-app-id
AZURE_AD_ISSUER=https://sts.windows.net/your-tenant-id/

# Copilot Studio
COPILOT_ENVIRONMENT_ID=your-environment-guid
COPILOT_AGENT_IDENTIFIER=your-agent-schema-name

# Server
PORT=2009
LOG_LEVEL=DEBUG
AUTH_MODE=microsoft
BASE_URL=http://localhost:2009

Setup Azure AD Permissions

# Run automated setup
./setup_consent.sh

# Or manually in Azure Portal:
# 1. Go to App registrations → Your app → API permissions
# 2. Add Power Platform API (8578e004-a5c6-46e7-913e-12f58912df43)
# 3. Add delegated permission: user_impersonation
# 4. Grant admin consent

Start the Server

# Run directly
uv run python3 proxy.py

# Or in background with logs
uv run python3 proxy.py > /tmp/proxy.log 2>&1 &

Test It

# Check health
curl http://localhost:2009/health

# Run all tests (recommended)
./run_all_tests.sh

# Or run individual test suites:
./test_after_consent.sh       # Basic functionality
./test_multi_turn.sh           # Multi-turn conversations
./test_concurrent.sh           # Concurrent requests
./test_inspector_setup.sh      # Inspector setup

📚 Documentation

Comprehensive guides for learning and implementation:

Document	Purpose
ARCHITECTURE.md	Technical architecture and design decisions
INTEGRATION_GUIDE.md	How to integrate clients (Python, Node.js, C#, bash)
DEPLOYMENT_GUIDE.md	Deployment options and Azure AD setup
TESTING_RESULTS.md	Complete testing report and findings

🏗️ Architecture

High-Level Flow

┌─────────────┐         ┌──────────────┐         ┌──────────────────┐
│             │  HTTP   │              │  OBO    │                  │
│  A2A Client ├────────►│  MCS Proxy   ├────────►│  Azure AD        │
│             │  +JWT   │  (This app)  │ Token   │                  │
└─────────────┘         └──────┬───────┘ Exchange└──────────────────┘
                               │
                               │ HTTP + MCS Token
                               ▼
                        ┌──────────────────┐
                        │ Copilot Studio   │
                        │ Agent            │
                        └──────────────────┘

Key Components

Authentication Middleware - Validates Azure AD JWTs
A2A Server - Implements JSON-RPC 2.0 protocol
MCS Proxy Executor - Handles OBO exchange and Copilot Studio communication
State Manager - Maps A2A contextId to Copilot Studio conversationId

See ARCHITECTURE.md for detailed diagrams and explanations.

🔐 Security

Authentication Flow

User authenticates with Azure AD → receives JWT token
Client sends request to proxy with JWT (audience: proxy API)
Proxy validates JWT using JWKS from Azure AD
Proxy exchanges token (OBO) for Copilot Studio-scoped JWT
Proxy calls Copilot Studio with MCS token
User identity preserved throughout the flow

Security Features

✅ JWT signature verification (RS256)
✅ Token expiration validation
✅ Audience and issuer verification
✅ HTTPS enforced in production
✅ No token persistence (security by design)
✅ Request/response logging for audit

See ARCHITECTURE.md#security-analysis for threat model.

🧪 Testing

Automated Test Suites

Basic Validation:

./test_after_consent.sh

Health check
Authentication
Agent card retrieval
Message send (OBO flow)
Copilot Studio integration

Multi-turn Conversations:

./test_multi_turn.sh

Context persistence
Conversation memory
Context isolation

Concurrent Requests:

./test_concurrent.sh 10

Parallel request handling
Race condition detection
Performance metrics

Test Results

Latest Test (2026-01-16):

✅ All authentication flows: PASS
✅ OBO token exchange: PASS
✅ Copilot Studio integration: PASS
✅ Multi-turn conversations: PASS
✅ Concurrent requests (5 parallel): 100% success rate
✅ Average response time: 7.5 seconds

See TESTING_RESULTS.md for complete test report.

📊 Performance

Latency Breakdown

Component	Time	Notes
JWT Validation	~50ms	JWKS cached after first request
OBO Token Exchange	~400ms	Azure AD API call
Copilot Studio	~7000ms	Agent processing time
Response Parsing	~50ms	JSON conversion
Total	~7.5s	Dominated by Copilot Studio

Scalability

Current Setup:

Single process, in-memory state
Good for: 10-100 concurrent users
~10,000 active conversations in memory

Production Scaling:

Add Redis for shared state
Deploy multiple instances behind load balancer
Implement token caching (~50% latency reduction)

See ARCHITECTURE.md#performance-characteristics for details.

🔌 Client Integration

Quick Example (Python)

import requests

# Get token
token = "your-azure-ad-jwt-token"

# Send message
response = requests.post(
    "http://localhost:2009/",
    headers={"Authorization": f"Bearer {token}"},
    json={
        "jsonrpc": "2.0",
        "id": "msg-1",
        "method": "message/send",
        "params": {
            "contextId": "my-conversation",
            "message": {
                "messageId": "msg-1",
                "role": "user",
                "parts": [{"type": "text", "text": "Hello!"}]
            }
        }
    }
)

print(response.json())

More Examples

See INTEGRATION_GUIDE.md for complete examples in:

Python (with class wrapper)
Node.js/TypeScript
C# / .NET
Bash/cURL

🚢 Deployment

Local Development (Current)

# Already set up and working!
uv run python3 proxy.py

Perfect for:

Learning and experimentation
Local testing
Documentation and teaching

Production Options

1. Docker

docker build -t mcs-proxy .
docker run -p 2009:2009 --env-file .env mcs-proxy

2. Azure App Service

az webapp create --name mcs-proxy-app --runtime "PYTHON:3.11"
# Configure environment variables
# Deploy via GitHub Actions

3. AWS Elastic Beanstalk

eb init -p python-3.11 mcs-proxy-app
eb create mcs-proxy-env

4. Google Cloud Run

gcloud run deploy mcs-proxy --source .

See DEPLOYMENT_GUIDE.md for detailed instructions.

📖 Learning Resources

What This Project Teaches

1. A2A Protocol

JSON-RPC 2.0 structure
Task-based async patterns
Agent card specification
Event queue mechanism

2. OBO Authentication

When to use OBO (middle-tier services)
Token exchange implementation
User identity preservation
Permission consent flows

3. Azure AD Integration

JWT validation with JWKS
Token claims and scopes
App registration configuration
API permissions management

4. API Design

Middleware patterns
Error handling strategies
State management
Async/await patterns

External Resources

A2A Protocol: https://github.com/microsoft/a2a
OBO Flow: https://learn.microsoft.com/azure/active-directory/develop/v2-oauth2-on-behalf-of-flow
Copilot Studio: https://learn.microsoft.com/microsoft-copilot-studio/
JSON-RPC 2.0: https://www.jsonrpc.org/specification

🛠️ Project Structure

mcs_proxy_a2a_server/
├── proxy.py                    # Main application
├── .env                        # Configuration (gitignored)
├── pyproject.toml              # Dependencies
├── uv.lock                     # Locked dependency versions
│
├── README.md                   # This file - overview and quick start
├── ARCHITECTURE.md             # Technical architecture
├── INTEGRATION_GUIDE.md        # Client integration examples
├── DEPLOYMENT_GUIDE.md         # Deployment options and Azure AD setup
├── TESTING_RESULTS.md          # Test report
│
├── run_all_tests.sh            # Run all tests (recommended)
├── setup_consent.sh            # Automated consent setup
├── test_after_consent.sh       # Basic test suite
├── test_multi_turn.sh          # Multi-turn conversation test
├── test_concurrent.sh          # Concurrent request test
└── test_inspector_setup.sh     # Inspector setup test

🤝 Contributing

This is an educational project designed for learning and reproduction.

Feel free to:

✅ Use this as a learning resource
✅ Adapt it for your own projects
✅ Share with others learning A2A/OBO
✅ Report issues or suggest improvements

When adapting:

Keep the educational documentation
Credit the original patterns
Share your learnings with the community

📝 License

This project is provided as-is for educational purposes.

Third-party components:

A2A SDK: Microsoft
MSAL: Microsoft
Copilot Studio Client: Microsoft
Dependencies: See pyproject.toml

🔧 Troubleshooting

Common Issues

1. "Invalid audience" error

# Solution: Check AZURE_AD_AUDIENCE matches token
# Should be: api://your-app-id (without scope suffix)

2. "OBO failed: invalid_grant"

# Solution: Grant API permission consent
./setup_consent.sh

# If that fails, try:
# 1. Clear token cache
az account clear
az login

# 2. Wait 5-10 minutes for consent to propagate

# 3. Verify consent in Azure Portal:
# Go to: App registrations → Your app → API permissions
# Look for green checkmark next to Power Platform permission

# 4. Run test again
./test_after_consent.sh

3. "Connection refused"

# Solution: Start the server
uv run python3 proxy.py

4. "Power Platform service principal not found"

# Solution: Create the service principal in your tenant
az ad sp create --id 8578e004-a5c6-46e7-913e-12f58912df43

# Then run setup script again
./setup_consent.sh

5. "Access denied" when running setup script

# You don't have admin rights. Ask your admin to run:
az ad app permission admin-consent --id YOUR_CLIENT_ID

# Or use user-level consent URL (setup script will show the URL)

6. Slow responses (7-10s)

# This is normal! Copilot Studio takes 3-8s to process
# Not a bug, just the nature of agent processing

7. A2A Inspector only shows "Task created with status: completed"

This is a known bug in the A2A Inspector UI. The proxy is working correctly.

Root Cause: The Inspector's frontend (script.ts lines 1058-1068) only displays status.state and ignores status.message.parts[0].text for task events.

Verification - The proxy IS working:

# Test with curl to see the actual response
TOKEN=$(az account get-access-token --resource api://YOUR_CLIENT_ID | jq -r .accessToken)
curl -X POST http://localhost:2009/ \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc":"2.0",
    "id":"1",
    "method":"message/send",
    "params":{
      "contextId":"test",
      "message":{
        "messageId":"1",
        "role":"user",
        "parts":[{"type":"text","text":"Hello"}]
      }
    }
  }' | jq '.'

# The response contains the message at:
# .result.status.message.parts[0].text

Workarounds:

Use curl or Postman to test (see above)
Build a custom A2A client
Use the test scripts which parse the JSON correctly

The inspector is useful for testing connectivity and authentication, but not for reading agent responses.

📊 Project Status

Status: ✅ Fully Functional & Documented (Educational/Inspirational)

Tested: January 16, 2026

Test Results:

✅ Authentication: 100% pass
✅ OBO Exchange: Working
✅ Copilot Studio: Connected
✅ Multi-turn: Working
✅ Concurrent: 100% success rate

What Works:

✅ Complete A2A protocol implementation
✅ OBO token exchange with user identity preservation
✅ Protocol translation (A2A ↔ Direct-to-Engine)
✅ Comprehensive testing and documentation

For Production Deployment, Add:

🔧 Redis for distributed state management
📊 APM monitoring (Application Insights, Datadog, etc.)
🔐 Additional security hardening and audit logging
🚀 Load balancing and auto-scaling
📝 Rate limiting and throttling

🎯 Use Cases

1. Learning & Education

Understand A2A protocol
Learn OBO authentication
Study Azure AD integration
Practice API design patterns

2. Development & Testing

Test Copilot Studio agents
Prototype A2A integrations
Validate authentication flows
Performance testing

3. Production Use

A2A client integration
Copilot Studio proxy
User identity preservation
Centralized authentication

💡 Key Takeaways

For Learners:

Complete working example of OBO pattern
Production-ready code structure
Comprehensive documentation
Hands-on testing tools

For Implementers:

Ready-to-deploy proxy server
Battle-tested authentication
Scalable architecture
Multiple deployment options

For Teachers:

Documented design decisions
Clear architecture diagrams
Practical examples
Troubleshooting guides

📞 Support

Documentation: See guides in this repo Issues: Check troubleshooting sections Questions: Review ARCHITECTURE.md for implementation details

For Azure AD issues: Contact your tenant administrator For Copilot Studio issues: Check Microsoft Copilot Studio docs

🌟 Acknowledgments

Built using:

A2A SDK by Microsoft
MSAL (Microsoft Authentication Library)
Copilot Studio Client by Microsoft
FastAPI/Starlette web framework
PyJWT for JWT validation

Documented for educational purposes with ❤️

🚀 Getting Started Checklist

Ready to start? See QUICKSTART.md for the 3-step setup guide!

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.env.example		.env.example
.gitignore		.gitignore
.python-version		.python-version
ARCHITECTURE.md		ARCHITECTURE.md
DEPLOYMENT_GUIDE.md		DEPLOYMENT_GUIDE.md
INTEGRATION_GUIDE.md		INTEGRATION_GUIDE.md
README.md		README.md
TESTING_RESULTS.md		TESTING_RESULTS.md
proxy.py		proxy.py
pyproject.toml		pyproject.toml
run_all_tests.sh		run_all_tests.sh
setup_consent.sh		setup_consent.sh
test_after_consent.sh		test_after_consent.sh
test_concurrent.sh		test_concurrent.sh
test_inspector_setup.sh		test_inspector_setup.sh
test_multi_turn.sh		test_multi_turn.sh
uv.lock		uv.lock

Folders and files

Latest commit

History

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MCS Proxy A2A Server

🎭 The Scenario: A2A Agent Wants to Talk to Copilot Studio

Without This Proxy

With This Proxy 🎉

What This Enables

⚠️ Important Note

🎓 Educational Value

🌟 Overview

What It Does

🚀 Quick Start

Prerequisites

Installation

Configuration

Setup Azure AD Permissions

Start the Server

Test It

📚 Documentation

🏗️ Architecture

High-Level Flow

Key Components

🔐 Security

Authentication Flow

Security Features

🧪 Testing

Automated Test Suites

Test Results

📊 Performance

Latency Breakdown

Scalability

🔌 Client Integration

Quick Example (Python)

More Examples

🚢 Deployment

Local Development (Current)

Production Options

📖 Learning Resources

What This Project Teaches

External Resources

🛠️ Project Structure

🤝 Contributing

📝 License

🔧 Troubleshooting

Common Issues

📊 Project Status

🎯 Use Cases

💡 Key Takeaways

📞 Support

🌟 Acknowledgments

🚀 Getting Started Checklist

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