Join us as Sam demonstrates how to teach AI to write Terraform configurations using Model Context Protocol (MCP) servers.

Sam introduces the Terraform MCP server and walks through practical demos showing how AI can understand and safely interact with your infrastructure. You'll see live examples of AI planning, generating, and evolving Terraform configurations - from creating landing zones to setting up workspace variables automatically. Whether you're managing complex multi-cloud environments or just getting started with infrastructure as code, this episode demonstrates how MCP servers bridge the gap between AI capabilities and real-world Terraform workflows. Learn how to get started, which Claude models work best for different tasks, and best practices for integrating AI into your IaC pipelines.

Timestamps

0:00 Welcome & Introduction

4:37 Sam McGeown's Background

6:02 Introduction to Terraform MCP Server

12:35 What is Model Context Protocol?
18:22 Setting Up the Terraform MCP Server
24:16 Demo: Claude Desktop Integration
30:41 Creating Infrastructure with AI Prompts
36:52 Reading & Analyzing Existing Terraform Code
42:18 Generating Landing Zone Configurations
47:35 Working with Terraform Workspaces
50:37 Creating Variables Automatically
52:14 Model Selection: Sonnet vs Opus
55:11 Live Demo: Workspace Variable Creation
58:33 Getting Started & Resources

How to find Sam:

https://www.linkedin.com/in/sammcgeown/

Links from the show:

https://developer.hashicorp.com/terraform/mcp-server

Teaching AI to Terraform (So We Don't Have To)