CLI and MCP Basics for AI Agents (The Context Window #04)

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MCP vs CLI: which one should your AI agent actually use? In this episode of The Context Window — Grafana’s livestream series on AI in observability — I’m joined by Tiffany Jernigan and three of the engineers and PMs behind Grafana’s agent tooling: Ben Sully (who wrote the Grafana MCP server), and Ward Bekker and Dafydd Thomas from the team building gcx. We get into the two main ways an AI agent can reach the outside world — the Model Context Protocol (MCP) and good old command-line interfaces — and look at when each one makes sense, the tradeoffs around context windows, tool sprawl, token cost, and reliability. We walk through Grafana’s cloud and open-source MCP servers along with gcx, the Grafana Cloud CLI built for agents, do a live side-by-side demo of both creating an SLO, and talk about how we benchmark them against each other with o11y-bench.

Timestamps

  • 00:00:00 — Introductions
  • 00:02:49 — The last month in AI news
  • 00:10:19 — What is Grafana Assistant?
  • 00:12:30 — What does it mean for Assistant to use tools?
  • 00:13:30 — What is MCP?
  • 00:16:56 — What is a CLI in an AI context?
  • 00:19:17 — What are skills?
  • 00:24:37 — Can you use a custom MCP server with Grafana Assistant?
  • 00:25:55 — Why team MCP?
  • 00:28:22 — The context-window cost of MCP tool definitions
  • 00:31:50 — Tool discoverability
  • 00:39:25 — What is gcx, and why a CLI?
  • 00:46:13 — Demo: creating an SLO with MCP vs gcx
  • 00:52:58 — Benchmarking MCP vs gcx with o11y-bench
  • 00:58:10 — How MCP and gcx relate to Grafana Assistant
  • 01:02:35 — k6 MCP vs Grafana MCP
  • 01:03:00 — When to use which (decision guide)
  • 01:04:29 — Adding the OSS Grafana MCP to Assistant
  • 01:05:41 — Turtles all the way down

Resources

MCP and CLI for agents

More from The Context Window

See Also