Labs MCP · Model Context Protocol
Labs MCP connects AI tools to iximiuz Labs, where they can coach you through hands-on learning, build custom playgrounds from plain-English prompts, and give coding agents real Linux VMs for real server-side work.
https://labs.iximiuz.com/mcpWorks with Claude, ChatGPT, Codex, Cursor, opencode — any MCP client. And you decide exactly what it's allowed to do. Connection instructions ↓
› Spin up a Docker playground and run nginx on port 80.
✓start_play(docker) — docker-01 ready in 3s
✓run_shell_command(docker run -d -p 80:80 nginx)
✓expose_port(80 · public)
↳ https://…-a1b2c3.iximiuz.com
nginx is live — open the URL above. Want me to spin up another container or clone a GitHub repo?
›
Four things it does
chapter 01 · learn
Tell your assistant what you're trying to learn. It searches the Labs catalog, assembles a plan that fits your background and your schedule — and when you get stuck, it acts like an infinitely patient mentor: right there in the same VM, nudging you forward with hints, not answers.
Your assistant can search the entire Labs catalog — tutorials, challenges, courses, skill paths. Tell it what you're after, and it'll pick the materials that match your level.
› Find me hands-on material about container networking — I already know the Docker basics.
There's no one-size-fits-all approach to learning. Tell your assistant where you are and where you want to get, and it'll assemble a personal learning path from Labs materials and pace you through it.
› Build me a two-week plan to get comfortable with Kubernetes — one hour a day, hands-on only.
Stuck mid-challenge, or a tutorial step isn't clicking? Your coach checks your task state, runs diagnostics in the same VM, and nudges you toward the next step — hints first, never the full solution.
› I'm stuck on the NAT challenge — the container pings the host but nothing outside. Hint please.
Progress is recorded server-side — streaks, completions, and daily practice stay in sync whether you learn in the browser or through your assistant.
chapter 02 · practice
Preparing a practice environment used to be a chore: writing init scripts, baking rootfs images, debugging the boot. Now it's a sentence: name the machines, the software, even the failure you want to debug — and your agent assembles the playground for you.
One VM, Docker preinstalled, a sample app already running behind a reverse proxy — ready for you to explore, break, and rebuild.
› Give me a Docker host with a small web app behind nginx — I want to practice tweaking reverse proxies.
A real K3s cluster with the tooling you asked for installed and wired up before you even open the terminal.
› Start the K3s playground, helm-install Argo CD, and give me the UI URL and the admin password.
Nothing teaches better than fixing a broken system. Ask your agent to sabotage a deployment, then debug it yourself — and let the agent verify your fix.
› Deploy a demo microservice app on K0s and break it in three subtle ways. Don't tell me what you broke.
Liked a setup? Ask your agent to save it as a reusable playground and start it again with one call.
chapter 03 · build
Coding agents are great at writing server-side code — and surprisingly bad at running it, because a typical agent sandbox is a locked-down container. Here's how the options stack up:
A confined container with a slice of a filesystem. Fine for code snippets; hopeless for realistic server-side projects.
A real Linux VM — your agent can install packages and run services. But it's usually a black box: you can't SSH in, watch what the agent is doing, or keep anything it built.
Up to five real Linux VMs (Firecracker-powered, same as every Labs playground), connected into whatever network topology the task requires — and optionally pre-provisioned with software of arbitrary complexity: a Kubernetes cluster with Helm charts installed, a service mesh, a system broken on purpose. Sized for real server-side and DevOps work — deployments, clusters, networks — not just code snippets.
And unlike the black-box cloud sandboxes, you see — and keep — everything:
They're your VMs, not a black box. Watch your agent work, take over mid-task, or pair with it in the same terminal.
Anything listening on a port becomes a shareable HTTPS URL — demo what your agent just built.
Persist the rootfs when you stop. Packages, data, half-finished work — the whole environment is there when you come back.
A fresh Labs VM with real internet access as a scratch pad — test a script, reproduce a bug, try a tool. No local setup.
› My install script works on Ubuntu but dies on Alpine. Start both VMs and find where they diverge.
Point your agent at a repository. It clones, builds, and runs the app, then exposes the port as a public HTTPS URL you can open.
› Clone my side project from GitHub, build and run it, then give me a public URL I can send around.
A load balancer in front of two app nodes? A cluster plus an external client machine? Your agent wires up the machines and networks it needs.
› Set up a 3-tier app across five VMs — an LB, two instances of the API service, and a replicated DB.
chapter 04 · create PRO
iximiuz Labs isn't just for learners — authors publish hands-on tutorials and challenges here, and trainers run whole courses and workshops. Labs MCP brings an assistant into that workflow, too.
Publishing on iximiuz Labs? Draft tutorials, challenges, courses, and blog posts straight from your AI tool — the author tools work against your real author profile, and drafts land in your usual review flow.
› Draft a challenge where the student fixes a crashing systemd service — write the description and tasks, I'll review.
Running trainings or cohorts on Labs? Instructor assistance — course scaffolding, per-student environments, progress digests — is on its way.
Training on iximiuz Labs →Connect in a minute
Labs MCP is a standard remote MCP server (Streamable HTTP + OAuth) — if your AI tool speaks MCP, it can connect. Pick yours:
First protected action shows a consent screen listing exactly what's requested. Revoke anytime under Account → Connected apps.
Permissions
Commands run only in playgrounds you own — your own sandbox — and every token is revocable.
accountauthorlearningplaygroundThe toolbox
Everything above boils down to plain MCP tools. Expand to browse the full list — with example prompts for each.
Open access
› Find beginner-friendly Kubernetes challenges on iximiuz Labs.
› Is there anything hands-on about eBPF on Labs?
› What's the 'Reproduce a Docker Bridge Network' challenge about — and how hard is it?
› How does playground persistence work? Check the Labs docs.
Read learning:read
› I'm on task 2 of the NAT challenge and iptables looks right to me — what am I missing?
› Explain what this task actually wants from me.
Write learning:write
› Start the 'Set Up NAT for a Container' challenge.
› Enroll me in the Docker The Hands-On Way roadmap.
› I've finished the bridge networking tutorial — mark it done.
Read playground:read
› I need kernel 6.1 for eBPF stuff — which kernels are available?
› Any RHEL-like base images — Rocky or Alma?
› Which official Kubernetes playgrounds are there?
› List my custom playgrounds.
› Do I still have that K3s playground from yesterday?
› How many nodes does the k3s playground have, and what's preinstalled?
› Is my playground done booting? When does it expire?
› How far am I in this challenge — which tasks are still failing?
Write playground:write
› Start the Docker playground.
› Give me a clean Ubuntu 24.04 VM.
› Install nginx and curl localhost to check it's up.
› Run kubectl get pods -A and tell me what's crashlooping.
› Drop a docker-compose.yml with the app and Redis into /root.
› Expose port 3000 so I can open the app on my phone.
› Give me a browser terminal to this VM — I want to poke around myself.
› Don't let this playground vanish when the timer runs out.
› I'm done for today — stop the playground but keep my work.
› Bring back the cluster I stopped on Friday.
› I don't need this scratch VM anymore — destroy it.
› Title this run 'issue #423 repro'.
› The demo is at 5pm — give this play two more hours.
› Make me a reusable playground: Ubuntu with Go, Docker, and my dotfiles.
› Add a second VM to my custom playground for the database.
› Delete my scratch custom playground.
› Snapshot this setup as a playground so my study group can start from it.
Read account:read
› What plan am I on?
› Did I keep my streak alive this week?
› What's my daily practice today?
Write account:write
› Today's challenge is too hard — reshuffle my daily practice.
› Switch my digest to weekly.
Read author:read
› Do I have an author profile yet?
Write author:write
› Set me up with an author profile called Jane Doe.
› Update my author bio to mention I write about eBPF.
› Start a draft tutorial titled 'Debugging DNS Inside Containers'.
one url · any mcp client
Add the connector URL to your AI tool and start building. Happy hacking!
https://labs.iximiuz.com/mcp