# Exploring MCP Tooling for Debugging and Observability in Kubernetes Clusters

- Institution: CERN
- Speaker: Elisa Marzioli
- Year: 2026
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3026659)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

**Project Description**:

Kubernetes clusters are becoming increasingly complex, making debugging and fixing issues difficult. We would like to explore the emerging capabilities of agentic AI tooling for interacting with and diagnosing issues in Kubernetes clusters. The project aims to show how MCP-based tooling can make complex systems easier to work with: by giving guidance on how clusters are set up, providing suggestions on how clusters could be optimised (e.g. how best to bin pack nodes, security reconfigurations etc) and suggesting preventative measures to make clusters more resilient to future incidents. The outcome of this project will be an evaluation of the current landscape of MCP tooling for working with Kubernetes broken down by their use cases whilst assessing the feasibility to integrate with the existing MCP based tooling within the section.

**Supervisor**: Jack Charlie Munday, Diana Gaponcic

00:00:00 Slide 1

00:00:24 Slide 2

00:00:41 Slide 3

00:01:03 Slide 4

00:02:39 Slide 5

00:04:44 Slide 6

00:05:16 Slide 7

## Lectures

1. [Exploring MCP Tooling for Debugging and Observability in Kubernetes Clusters](https://invisiblenetwork.ai/learn/cern/3026659/5dcb5fc7ff28), 8 min (CERN's player)