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Agentic AI Protocols: MCP, ACP & A2A

2-Week Nanodegree Module

Module Overview

This self-paced 2-week module provides comprehensive instruction on building production-ready agent communication systems using the Model Context Protocol (MCP), Agent Communication Protocol (ACP), and Agent-to-Agent (A2A) protocols. Through hands-on tutorials and practical examples, you'll develop skills to create interoperable, distributed agent architectures.

Distributed Agent Systems

Prerequisites

  • Completed Agent Frameworks module
  • Completed RAG module
  • Python programming experience (intermediate level)
  • Basic understanding of HTTP/REST APIs
  • Familiarity with LLM APIs and JSON-RPC protocols
  • Experience with virtual environments and package management

Week 1: MCP Fundamentals & Implementation

Session 0: Introduction to MCP, ACP, and A2A (Self-Study)

Content: Understanding the agent communication ecosystem, M×N integration problem, and protocol overview Materials: Session0_Introduction_to_MCP_ACP_A2A.md Self-Check: 15-question multiple choice quiz covering core concepts

Session 1: Building Your First MCP Server

Content: Hands-on creation of weather information MCP server with tools, resources, and prompts Materials: Session1_Basic_MCP_Server.md + Session1_Basic_MCP_Server-solution.md Self-Check: Multiple choice quiz covering MCP server development concepts

Session 2: File System MCP Server

Content: Building advanced MCP server with file operations, error handling, and security Materials: Session2_FileSystem_MCP_Server.md + Session2_FileSystem_MCP_Server-solution.md Self-Check: Multiple choice quiz covering file system integration and security

Session 3: LangChain MCP Integration

Content: Client development patterns, tool discovery, and framework integration Materials: Session3_LangChain_MCP_Integration.md + Session3_LangChain_MCP_Integration-solution.md Self-Check: Multiple choice quiz covering client integration patterns

Session 4: Production MCP Deployment

Content: Containerization, cloud deployment, authentication, and monitoring Materials: Session4_Production_MCP_Deployment.md + Session4_Production_MCP_Deployment-solution.md Self-Check: Multiple choice quiz covering deployment and production concerns

Session 5: Secure MCP Server

Content: Authentication strategies, input validation, rate limiting, and security best practices Materials: Session5_Secure_MCP_Server.md + Session5_Secure_MCP_Server-solution.md Self-Check: Multiple choice quiz covering security implementation


Week 2: ACP & A2A Agent Communication

Session 6: Agent Communication Protocol (ACP) Fundamentals

Content: ACP architecture, local agent discovery, edge deployment, and framework integration Materials: Session6_ACP_Fundamentals.md + Session6_ACP_Fundamentals-solution.md Self-Check: Multiple choice quiz covering ACP concepts and local coordination

Session 7: Agent-to-Agent Communication (A2A)

Content: A2A protocol fundamentals, agent discovery, communication patterns, and multi-agent coordination Materials: Session7_Agent_to_Agent_Communication.md + Session7_Agent_to_Agent_Communication-solution.md Self-Check: Multiple choice quiz covering A2A protocol and agent communication

Session 8: Advanced Agent Workflows

Content: Complex multi-agent orchestration, workflow patterns, and advanced coordination techniques Materials: Session8_Advanced_Agent_Workflows.md + Session8_Advanced_Agent_Workflows-solution.md Self-Check: Multiple choice quiz covering advanced workflow patterns

Session 9: Production Agent Deployment

Content: Deploying distributed agent networks with fault tolerance, scaling, and monitoring Materials: Session9_Production_Agent_Deployment.md + Session9_Production_Agent_Deployment-solution.md Self-Check: Multiple choice quiz covering production deployment strategies

Capstone Project: Distributed Agent Ecosystem

Project Overview: Build a comprehensive multi-agent system demonstrating MCP, ACP, and A2A integration

Requirements: - Implement local agent coordination using ACP - Create MCP servers for data access and tool integration - Enable A2A communication for cross-platform collaboration - Deploy to production environment with monitoring

Deliverables: - Complete source code with documentation - Working deployment with monitoring dashboard - Architecture documentation and API specifications


Comprehensive Resource Library

Core Documentation

Video Tutorials

Hands-on Tutorials

Advanced Reading

Code Repositories


Learning Outcomes

By completion, students will be able to:

Technical Skills

  1. Design and implement MCP servers with tools, resources, and prompts
  2. Create MCP clients that integrate with multiple servers
  3. Implement ACP coordination for local agent orchestration
  4. Enable A2A protocol for cross-platform agent communication
  5. Deploy distributed agent systems to cloud and edge platforms
  6. Secure agent communications with authentication and validation

Architectural Understanding

  1. Differentiate between MCP, ACP, and A2A use cases and environments
  2. Design interoperable agent ecosystems for cloud and edge deployment
  3. Implement proper separation of concerns between protocols and agents
  4. Plan for scalability and fault tolerance in distributed and offline systems

Industry Readiness

  1. Follow protocol specifications and best practices
  2. Debug multi-agent communication issues
  3. Monitor and maintain production agent systems
  4. Evaluate trade-offs between different architectural approaches

Self-Assessment Structure

Knowledge Checks

Each session includes multiple choice quizzes to verify understanding of key concepts: - Session 0: 15 questions covering MCP, ACP, and A2A fundamentals - Sessions 1-9: 8-12 questions per session covering specific implementation topics - Capstone Project: Self-evaluation checklist for project completeness

Practical Validation

  • Code Examples: Each session provides working code examples with solutions
  • Hands-on Tutorials: Step-by-step implementation guides for all major concepts
  • Self-Check Activities: Verify your implementations work as expected

Progress Tracking

  • Complete all session materials and quizzes to demonstrate mastery
  • Successfully implement and test all code examples
  • Build and deploy the capstone project following provided specifications

Development Environment Setup

Required Software

# Python environment
python3.11+
pip install fastmcp langchain-mcp-adapters a2a-python-sdk

# Node.js (for TypeScript MCP development)
node18+
npm install @modelcontextprotocol/sdk

# Cloud tools
gcloud CLI
docker
  • IDE: VS Code with MCP extension
  • API Testing: Postman or curl
  • Monitoring: Prometheus + Grafana
  • Version Control: Git with GitHub/GitLab

Development Workflow

  1. Local Development: Use stdio transport for rapid iteration
  2. Integration Testing: Deploy to local containers
  3. Production Deployment: Cloud platforms with proper monitoring

Completion Requirements

To successfully complete this nanodegree module: 1. Study all session materials (Sessions 0-9) 2. Complete all multiple choice quizzes with satisfactory scores 3. Successfully implement all code examples and tutorials 4. Build and deploy the capstone project demonstrating integration of all three technologies

Completion Recognition: "MCP, ACP & A2A Nanodegree Module Certificate"


Self-Study Support

Available Resources

  • Comprehensive Documentation: Each session includes detailed explanations and examples
  • Solution Code: Complete implementations provided for all exercises
  • External References: Curated links to official documentation and tutorials
  • Community Resources: Links to relevant GitHub repositories and developer communities

Learning Path

  1. Week 1: Master MCP fundamentals through hands-on server and client development
  2. Week 2: Explore ACP coordination patterns and A2A protocol implementation
  3. Capstone: Integrate all technologies in a production-ready distributed system

This module provides comprehensive, self-paced instruction on the cutting-edge protocols shaping the future of agentic AI systems. You'll gain practical experience building interoperable agent architectures that work in cloud, edge, and offline environments.