The MCP Learning Path

A Guide to Architecting Agentic AI Infrastructure

Explore these guides for a clear, step-by-step introduction to the Model Context Protocol (MCP). Begin at the basics to build your foundation, or skip ahead to topics you find most relevant. Each guide covers essential elements for creating, deploying, and managing scalable, collaborative AI agent systems.

1.

What Is an MCP Server? A Primer

Begin here to grasp the core idea of MCP and its key function as the 'tool and context interface' for agentic AI.

2.

MCP Server Architecture Deep Dive

Discover essential architectural elements—from the Tool Registry to the Routing Engine—needed to build scalable multi-agent systems.

3.

The Agent-as-Server Pattern

Experience a dynamic paradigm: every agent becomes its own MCP server, sharing skills as tools in a collaborative, peer-driven network.

4.

Integrating MCP with A2A Communication

Discover how Agent-to-Agent (A2A) protocols enhance MCP, unlocking advanced dialogue, negotiation, and genuine agent collaboration.

5.

Designing an Agentic Mesh

Advance past basic integrations to architect a robust, distributed system of expert agents and MCP servers collaborating seamlessly at enterprise scale.

6.

Tutorial: Building a Minimal MCP Server

Turn theory into action with this guide for creating a working MCP server from scratch using Python and FastAPI.

7.

Deploying MCP Servers in the Cloud

Understand key strategies for deploying agentic systems in production using cloud-native tools such as containers and autoscaling.

8.

MCP on Azure

Discover ways to create and expand agentic AI solutions for enterprises using Microsoft Azure’s platform, featuring Azure Functions and Semantic Kernel.

9.

Extending MCP for Domain-Specific Applications

Harness MCP’s full potential for advanced fields—finance, healthcare, IoT—by customizing schemas and enforcing compliance controls.

10.

Monitoring, Logging & Observability

Boost reliability and trust in MCP production servers by applying essential end-to-end tracing, monitoring, and auditing strategies.

11.

Security Risks in MCP

Discover key attack vectors such as code injection and data breaches, plus core strategies to defend against them within an MCP framework.

12.

MCP Guardian: Security Middleware

Introducing 'MCP Guardian'—a middleware solution serving as a unified gateway for authentication, rate control, and security threat management.

13.

Governance & Compliance in Multi-Agent Systems

Discover ways MCP can serve as a control hub for policy enforcement, audit tracking, and human-in-the-loop workflows to ensure responsible AI.

14.

Handling Malicious or Compromised MCP Servers

Master resilience and failover tactics, such as circuit breakers and adaptive trust scoring, to shield your ecosystem from malicious servers.

15.

MCP Use Cases in Enterprise Integration

Discover how MCP serves as a secure bridge, linking agents with enterprise systems such as CRM, ERP, and analytics tools.

16.

Collaborative Intelligence: Multi-Agent Teamwork

Learn to leverage an MCP server as a shared workspace, allowing teams of expert agents to collaborate and tackle challenging tasks together.

17.

Benchmarking MCP Server Performance

Move from theory to action by mastering the design and execution of robust benchmarks to evaluate your agentic infrastructure for latency and scalability.

18.

Migrating Legacy Tool Integrations to MCP

Master methods such as the 'Strangler Fig' to update your agentic stack and convert legacy APIs into MCP tools—no complete overhaul needed.

19.

The Agentic Web

Envision a future built on a decentralized web of intelligent agents, with MCP at its core powering this transformation.

20.

The MCP Research Frontier

Explore the key challenges and innovative research driving MCP's future, spanning semantic interoperability and hybrid system designs.