The MCP Learning Path

A Guide to Architecting Agentic AI Infrastructure

This collection of guides provides a step-by-step journey into the Model Context Protocol (MCP). Start from the beginning to build a solid foundation, or jump to the topic that interests you most. Each guide explores a key aspect of building, deploying, and managing scalable, collaborative AI agent systems.

1.

What Is an MCP Server? A Primer

Start here to understand the foundational concept of MCP and the crucial role it plays as the "tool and context interface" for agentic AI.

2.

MCP Server Architecture Deep Dive

Explore the core architectural components—from the Tool Registry to the Routing Engine—required to engineer scalable multi-agent systems.

3.

The Agent-as-Server Pattern

Discover a powerful new pattern where each agent acts as its own MCP server, exposing its skills as tools for a collaborative, peer-to-peer network.

4.

Integrating MCP with A2A Communication

Learn how Agent-to-Agent (A2A) protocols complement MCP to enable higher-level dialogue, negotiation, and true collaboration between agents.

5.

Designing an Agentic Mesh

Move beyond simple integrations to design a structured, distributed network of specialized agents and MCP servers that work in concert at enterprise scale.

6.

Tutorial: Building a Minimal MCP Server

Put theory into practice with this step-by-step guide to building a functional MCP server from scratch using Python and FastAPI.

7.

Deploying MCP Servers in the Cloud

Learn the patterns and best practices for deploying production-grade agentic systems using cloud-native principles like containerization and autoscaling.

8.

MCP on Azure

Explore how to build and scale enterprise-grade agentic AI by leveraging Microsoft Azure's ecosystem, including Azure Functions and Semantic Kernel.

9.

Extending MCP for Domain-Specific Applications

Unlock the true power of MCP by tailoring it for complex fields like finance, healthcare, and IoT with custom schemas and compliance guardrails.

10.

Monitoring, Logging & Observability

Ensure reliability and trust in production MCP servers by implementing key strategies for end-to-end tracing, monitoring, and auditing.