Deep Dive

MCP Internals: Visualizing Agent-Tool Architecture

11 interactive labs
Updated Jan 2026

See the Invisible

Interactive simulators visualize what's hidden from view.

Hands-On Labs

Step through executions tick by tick. Manipulate state.

Why, Not Just What

Deep architectural understanding for mid-senior developers.

AI Sandbox Lab

Real-world scenarios. Find the flaws AI misses.

The AI Era Demands More

Become the Engineer Who Supervises AI

As AI generates more code, understanding what that code does becomes more valuable, not less. Someone must verify AI output, debug failures, and make architectural decisions.

Build Your Architectural Edge

You've built AI applications. But do you know how they actually talk to the outside world?

MCP is the protocol layer that connects LLMs to tools, files, databases, and APIs. This course makes the invisible visible: watch messages flow through Host-Client-Server topologies, trace capability negotiation handshakes, and debug failures at every protocol boundary.

The Integration Chaos You Know Too Well

Every AI application faces the same problem: LLMs operate in isolation. They have no persistent awareness of your file system, databases, or external APIs. So you write bespoke integration code. Every tool gets its own error handling. Every API gets its own discovery logic. Capability negotiation becomes a maze of if-statements.

When something breaks, where do you look? Is it the transport layer? The message serialization? The tool handler? The capability mismatch during initialization? Without understanding the protocol architecture, you're debugging blind.

MCP (Model Context Protocol) solves this with a standardized protocol layer. One consistent language connecting any AI application to any external capability. But reading the spec doesn't give you intuition. You need to see it work.

Interactive Simulators That Show What Specs Cannot

Watch JSON-RPC messages flow from Host to Client to Server in real time. See capability negotiation handshakes unfold step by step. Trace a tool invocation through every protocol layer. Inject failures and observe exactly how disconnections propagate. These simulators turn abstract protocol concepts into observable system behavior you can manipulate and understand.

What This Course Covers

The Context Gap Problem

Why LLMs need a standardized protocol to escape isolation. Where MCP sits in the application stack and why ad-hoc integrations create brittleness.

Host-Client-Server Topology

The three-actor architecture with distinct responsibilities and security boundaries. How multi-server configurations work and why Clients maintain 1:1 Server connections.

JSON-RPC Message Grammar

How MCP uses JSON-RPC 2.0 for requests, responses, and notifications. The structure of every message type and how method names map to protocol operations.

Capability Primitives

Tools, Resources, and Prompts: the three things MCP servers expose. When to use each, how capability negotiation works at initialization, and access patterns for each type.

Full-Stack Debugging

Tracing messages across Host-Client-Server boundaries. Diagnosing initialization failures, capability mismatches, tool execution errors, and transport disconnections. Understanding JSON-RPC error codes and what information to collect at each layer.

Course Curriculum

16 lessons. 11 interactive labs. Every protocol concept visualized.

Course Toolkit
Quick Reference Card

Visual cheatsheet

AI Sandbox Lab

Practice verifying AI-generated code

What is MCP? The Big Picture
The Context Gap Problem: Why MCP Exists
Lab: MCP vs Direct API Integration
The Host-Client-Server Topology
Lab: Actor Roles and Message Routing in Multi-Server Architectures
JSON-RPC as MCP's Message Grammar
Lab: Request-Response Flow Through Protocol Layers
Lab: Notifications: One-Way Messages and Their Role
The Three Capability Primitives: Tools, Resources, and Prompts
Lab: Capability Negotiation at Initialization
Lab: Tool Invocation Lifecycle: From Intent to Result
Lab: Resource Access: Read Operations and Subscriptions
Lab: Prompt Retrieval: Templates and Argument Injection
Lab: Server-Initiated Sampling: The Reverse Flow
Lab: Diagnosing Failures Across the MCP Chain
Lab: Full-Stack Message Tracing: Observing a Live MCP System

Built for engineers who need to understand MCP at the protocol level: how capability discovery works, why the three-actor topology exists, and where to look when things break. Whether you're implementing MCP servers, debugging integration failures, or architecting multi-agent systems, this course gives you the mental model to reason about any MCP interaction from first principles.

Ready to see what's really happening?

All deep dives included with your subscription. Cancel anytime.