
Begin by setting up your development environment and configuring existing MCP server. Build MCP server from scratch in Python, extend it with SQLite, and test with VS Code and Copilot.
Install python on your system by checking with python --version, download from python.org for Windows or macOS, run the installer, and verify with python --version and where python.
Install Visual Studio Code to use as the editor for writing, running, and testing our MCP server code throughout this course.
Install pip, the package manager for Python, to download and manage the libraries for this course; verify with pip --version and install using python get-pip.py if needed.
Install UV to manage projects and virtual environments for the MCP server, verify the installation, and prepare UV for use in initializing MCP projects and environments.
Install and configure the Cloud Desktop client to connect, manage, and test MCP servers locally, then verify the installation and sign in, preparing for future node.js setup.
install and configure Node.js and npm to run MCP-related tools, verify installations via npm --version, and prepare your environment for subsequent verification in the next lecture.
Verify that Python, pip, uv, Node.js, npm, VS Code, and the Cloud Desktop client are installed correctly to ensure the environment is ready for MCP server building.
Configure an existing MCP server with the Cloud Desktop client and reload the configuration. Verify the server appears under settings and test by sending a prompt to trigger its behavior.
Learn to build and run an MCP server from scratch in Python, initialize a uv project, create a virtual environment, install the MCP library, and test locally with the dashboard.
Extend your MCP server with SQLite to enable local data storage and persistence, then configure the server, run it, and verify data retrieval via the browser dashboard.
Build and test an MCP server using resources by adding resource code, running locally, and validating the dashboard, then attach the resource in Cloud Desktop to answer prompts.
Set up a prompts-driven MCP server in VS Code and integrate the provided prompt file. Run locally to verify the local dashboard and cloud desktop client integration, testing prompt-based behavior.
Enable local streamable HTTP for the MCP server, expose it via a local endpoint, and verify access with the MCP dashboard, prepping for remote streamable HTTP deployment in next lecture.
Deploy your MCP server over remote streamable http to a public URL, then push to GitHub and deploy on render.com, testing the remote endpoint.
This course contains the use of artificial intelligence.
In this course, you will learn how to build a Model Context Protocol (MCP) server in Python from scratch through clear, hands-on, step-by-step lessons.
The course is designed as a build-first learning journey, where you start by setting up the complete development environment and gradually move toward building, extending, and testing multiple MCP server implementations.
Each section of the course maps directly to the book’s chapters, allowing you to follow the curriculum sequentially and build a working MCP server piece by piece.
What This Course Covers
You will begin by preparing a clean development environment and verifying all required tools. From there, you will move into configuring an existing MCP server and then progress toward building your own MCP server from scratch.
As the course advances, you will incrementally enhance your MCP server with different capabilities, including:
Database-backed MCP servers using SQLite
MCP servers that work with resources and prompts
MCP servers using local and remote streamable HTTP
Testing and validating MCP servers using VS Code and Copilot
Each stage builds on the previous one, ensuring a clear, structured, and progressive learning path.
Course Structure
The course follows this exact progression:
Install and configure all required software
Python, VS Code, PIP, UV
Claude Desktop Client
Node.js
Installation verification
Download and understand the complete book source code
Configure an existing MCP server
Finding and setting up an MCP server
Running it inside the Claude Desktop Client
Build and test your own MCP server from scratch
Creating the project
Running and validating the server
Extend your MCP server with SQLite
Adding persistence and storage
Build MCP servers using resources
Build MCP servers using prompts
Implement local streamable HTTP MCP servers
Implement remote streamable HTTP MCP servers
Test MCP servers using VS Code and Azure MCP Server
This structured approach ensures that you are always building, testing, and improving as you move forward.
Who This Course Is For
This course is ideal for:
Beginners who want to learn MCP by building from scratch
Python developers exploring MCP and AI tool integration
Learners following the book and wanting guided implementation
Developers who prefer structured, step-by-step learning
No prior MCP experience is required.
Basic Python familiarity is sufficient.
Learning Approach
Hands-on and practical
Step-by-step progression
Beginner-friendly
Build-from-scratch mindset
Curriculum-driven and structured
You will finish this course with real implementation experience and a clear understanding of how MCP servers are built, extended, and tested in practice.
Final Outcome
By the end of this course, you will have:
Built multiple MCP server implementations
Understood how MCP servers integrate with tools, resources, and prompts
Gained confidence to create and extend MCP servers on your own
Followed a complete, structured curriculum based on the book