Model Context Protocol servers. Connect AI to your tools and workflows. First comprehensive MCP course.
What you'll learn
✓ Build production-ready MCP servers that connect AI assistants (ChatGPT, Claude) to your AEC tools and data sources
✓ Implement MCP workflows combining local LLMs and cloud APIs for enterprise-grade AI integration architectures
✓ Develop custom MCP tools, resources, and prompts that expose your firm's data and systems to AI assistants
✓ Deploy and maintain MCP infrastructure using Vibe Coding methodology—building complex systems with AI collaboration
Requirements
● Solid coding foundation (Course 2) and Vibe Coding experience (Course 3) required—this is advanced technical content
● Understanding of APIs, web services, and client-server architecture helps but we'll explain concepts as needed
● Development environment with Python or Node.js ready (we support both FastMCP and TypeScript MCP SDK)
● Access to AI assistants (ChatGPT Pro or Claude Pro recommended for testing MCP integrations)
Description
Model Context Protocol (MCP) — Connect AI to Your Data
You've probably heard the term MCP. But what does it actually do?
Right now, AI assistants like Claude are powerful in general conversation — but they can't see your files, read your spreadsheets, or work with your private data. Every session starts from zero. MCP is the layer that changes that. It's a standardized protocol that lets AI talk to external tools and data sources. You define what the AI can access. It works locally, privately, on your terms.
Think of it like USB for AI: before USB, every device needed a different connector. After USB, everything just worked. MCP does the same for AI integration — one protocol, any data source.
This is not the last MCP course you'll take — it's the one that makes sure you take the right next one
What You'll Do in This Course
You won't be writing MCP servers from scratch. Three fully working servers are already built and waiting for you as reference — one for Word documents, one for Excel data, one for private document Q&A using a local AI model. What you'll do is run them, understand how they work, and extend them using Vibe Coding.
The course also comes with a complete set of rules, configurations, and Vibe Coding prompts — the same structured approach used to build the servers in the first place. Once you understand the pattern, you have everything you need to build your own integrations.
The Three Servers
- Word Connector — give Claude access to local Word documents: list, search, read, analyze
- Excel Processor — AI-powered data analysis through an HTTP API; works across Python and C#
- Document Intelligence — ask questions about your own PDF and Word files, answered by a local LLM running entirely on your machine, no cloud required
Prerequisites
This course assumes you have coding fundamentals and some experience with Vibe Coding. If you've completed Courses 1 and 2, you're ready. If you come from a coding background and have worked with AI-assisted development, that also works. If you don't have either yet — start there first, then come back. The concepts here build on both.
The Opportunity
MCP is early. Most developers haven't touched it. Most companies haven't figured out what it means for their workflows yet. The window where learning this gives you a real head start is open right now — not for long.
The deeper shift is this: AI that works with your actual data is a different category of tool than AI that answers general questions. When an AI assistant can read your documents, query your data, and work within your specific context — privately, without sending anything to a cloud you don't control — it stops being a productivity trick and starts being a genuine capability multiplier. This course is your entry point to building that.
After This Course
You'll have 3 working MCP servers, deep protocol understanding, and ability to build any integration needed. You'll be positioned as the MCP expert in your network.
Who this course is for
■ Professionals building AI-powered tools who need to connect MCP-based assistants to their existing workflows, tools, and data
■ Technical leads introducing MCP into day-to-day practice and needing production-grade integration, not experiments
■ Practitioners who've mastered Vibe Coding and want to design MCP systems that reliably connect assistants to internal tools, databases, and APIs
■ System designers and problem solvers who want a practical understanding of MCP to gain leverage in their daily work before it becomes a baseline skill