# [[Short - When to use Grafana Assistant vs MCP vs GCX]] <iframe width="560" height="315" src="https://www.youtube.com/embed/xo7meD4Yn0k" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> plugins:: "" Related:: "[[GCX]], [[Grafana MCP]], [[Grafana Assistant]]" ## Transcript Grafana has three AI things people keep confusing — Assistant, MCP, and GCX. I'm going to talk a bit about each one so you know which one is best for your use case. Spoiler: They're not competitors. Think of it as **a brain and two hands.** Let's start with **Grafana Assistant**, which is the brain. [B-ROLL: Assistant panel open in Grafana UI] It's not just a chatbot — it's the *reasoning layer*. It manages context, it knows your Grafana: your dashboards, your data sources, a knowledge graph of your infrastructure. So instead of you clicking around to do something, you can say what you want to do to Assistant and it figures out the *how.* [B-ROLL: typing a plain-English request] Reach for the Assistant when the work is **visual or exploratory.** - If you're building a dashboard? Assistant. [B-ROLL: dashboard building live] - "Teach me how to do this" or "where is this in the UI"? Assistant. - You have a real incident where you need root-cause analysis across multiple data sources? Assistant. - That's its sweet spot — it forms a hypothesis, correlates your signals, and can even open a pull request with the fix. [B-ROLL: RCA / multi-datasource nav] Here's the key thing though: Assistant is Grafana's *own* brain — but it's **not the only brain that can drive Grafana.** That's where the two hands come in… and I'll show you those next. %% ## Feedback ![[2026-08-20 [email protected]]] %%