Getting Started with Model Context Protocol (MCP)
Chapter 1: Architecture and Fundamentals
The MCP Specification Overview
Client-Host-Server Topology
JSON-RPC Message Structure
Transport Mechanisms: Stdio and SSE
Capabilities Negotiation
Hands-on Practice: Environment Setup
Chapter 2: Defining Resources and Prompts
Concept of Resources in MCP
URI Schemes and Patterns
Implementing Synchronous Resource Reads
Resource Subscriptions and Notifications
Structuring Prompts
Hands-on Practice: Building a File Reader Server
Chapter 3: Implementing Tools and Logic
Tool Definition Schema
Input Validation with Pydantic
Executing External API Calls
Error Handling and Reporting
Designing Computed Resources
Hands-on Practice: Creating a Database Tool
Chapter 4: Debugging and Client Integration
Using the MCP Inspector
Analyzing Log Output
Configuration for Claude Desktop
Managing Environment Variables
Handling Connection Lifecycles
Hands-on Practice: End-to-End Integration
Getting Started with Model Context Protocol (MCP)
Prerequisites Intermediate Python knowledge
Level:
Intermediate
MCP Architecture
Understand the Client-Host-Server relationship and the JSON-RPC message flow that underpins the protocol.
Server Implementation
Build functional MCP servers that expose static and dynamic data through Resources.
Tool Creation
Develop executable Tools that allow LLMs to perform actions and retrieve data from external APIs.
Client Integration
Configure and debug connections between custom MCP servers and standard clients like Claude Desktop.
There are no prerequisite courses for this course.
There are no recommended next courses at the moment.
Login to Write a Review
Share your feedback to help other learners.
© 2025 ApX Machine LearningEngineered with