Using MCP Servers with your Home Lab

Model Context Protocol (MCP), is one of the best ways for you to connect AI assistants directly to your infrastructure. It allows you to connect to the tools, solutions, and infrastructure running in a home lab or production environment. In this training video, I walk through some of my favorite MCP servers for the home lab in 2026 so far and show why they can drastically change the way you interact with your environments. It is a whole new way of managing environments like Proxmox, Kubernetes, GitHub, local files, documentation, and code repositories.

I show how MCP servers allow AI clients to go beyond just the simple question and answer chatbot workflows and allows AI to interact with real infrastructure using live data and platform APIs. I cover the Proxmox MCP Server and how it can be used to query virtual machines, containers, snapshots, cluster resources. Also see how you can get other Proxmox information using natural language. I also look at the GitHub MCP Server for looking at repositories and code. The Filesystem MCP Server is great for working with local project directories, and the Kubernetes MCP Server is very good for troubleshooting workloads, events, resource utilization, and application health.

The training also explores Context7 for showing how to make sure your docs use the current technical documentation in your AI-assisted workflows. We look at how to make your code and token use much more efficient as well with jcodemunch, jdatamunch, and jdocmunch for indexing and understanding code, documentation, and data. Along the way, I show practical config examples and we look at explaining how these MCP servers fit into a real home lab and DevOps workflow. I also discuss an important consideration when connecting AI to infrastructure. This includes security which you need to think about in limiting access and following the principle of least privilege. By the end of the video, you will have a much better understanding of what MCP servers are, which ones are useful for home lab environments. Also you will see how you can begin connecting them into your own infrastructure management workflows.