Analyze Kubernetes cluster issues through MCP with K8sGPT
Run K8sGPT as an MCP server so an agent can scan a Kubernetes cluster, explain unhealthy resources, and return prioritized remediation clues in natural language.
What it does
Analyze Kubernetes cluster issues through MCP with K8sGPT
Run K8sGPT as an MCP server so an agent can scan a Kubernetes cluster, explain unhealthy resources, and return prioritized remediation clues in natural language.
Prerequisites
A reachable Kubernetes cluster, K8sGPT, and an MCP-compatible client
Installation
Use the upstream install or setup path that matches your environment:
- brew install k8sgpt
- brew tap k8sgpt-ai/k8sgpt
- built from the source. k8sgpt Install Clang or run brew install gcc.
Requirements and caveats from upstream:
- K8sGPT can be integrated with Claude Desktop to provide AI-powered Kubernetes cluster analysis. This integration requires K8sGPT v0.4.14 or later.
- Analyzer Node took 160.109833ms
- Node
Basic usage or getting-started notes:
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If you install gcc as suggested, the problem will persist. Therefore, you need to install the build-essential package.
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Currently, the default AI provider is OpenAI, you will need to generate an API key from OpenAI
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Extracted from upstream docs: https://raw.githubusercontent.com/k8sgpt-ai/k8sgpt/HEAD/README.md
Documentation
Source
Capabilities
Install
Quality
deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 8 github stars · SKILL.md body (1,384 chars)