kubernetes-mcp-usage — community kubernetes-mcp-usage, kubernetes-mcp, community, ide skills

v1.0.0

About this Skill

Ideal for Cloud Agents requiring seamless Kubernetes integration through MCP for resource discovery and cluster state inspection Usage guide skill for kubernetes-mcp MCP server. Use when connecting the MCP server to clients, troubleshooting tool calls, and selecting the right Kubernetes tools for diagnosis and operations.

HSn0918 HSn0918
[0]
[0]
Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
47
Canonical Locale
en
Detected Body Locale
en

Ideal for Cloud Agents requiring seamless Kubernetes integration through MCP for resource discovery and cluster state inspection Usage guide skill for kubernetes-mcp MCP server. Use when connecting the MCP server to clients, troubleshooting tool calls, and selecting the right Kubernetes tools for diagnosis and operations.

Core Value

Empowers agents to connect MCP clients to Kubernetes servers via stdio, sse, or streamable protocols, enabling resource discovery, cluster state inspection, and log/event/metric checking through kubernetes-mcp-usage

Ideal Agent Persona

Ideal for Cloud Agents requiring seamless Kubernetes integration through MCP for resource discovery and cluster state inspection

Capabilities Granted for kubernetes-mcp-usage

Connecting MCP clients to Kubernetes servers
Discovering resources and inspecting cluster states
Troubleshooting failed tool calls and parameter mismatches

! Prerequisites & Limits

  • Requires reachable Kubernetes server
  • Confirmed kubeconfig for stdio connections
  • Accessible endpoint for streamable connections

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is kubernetes-mcp-usage?

Ideal for Cloud Agents requiring seamless Kubernetes integration through MCP for resource discovery and cluster state inspection Usage guide skill for kubernetes-mcp MCP server. Use when connecting the MCP server to clients, troubleshooting tool calls, and selecting the right Kubernetes tools for diagnosis and operations.

How do I install kubernetes-mcp-usage?

Run the command: npx killer-skills add HSn0918/kubernetes-mcp/kubernetes-mcp-usage. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for kubernetes-mcp-usage?

Key use cases include: Connecting MCP clients to Kubernetes servers, Discovering resources and inspecting cluster states, Troubleshooting failed tool calls and parameter mismatches.

Which IDEs are compatible with kubernetes-mcp-usage?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for kubernetes-mcp-usage?

Requires reachable Kubernetes server. Confirmed kubeconfig for stdio connections. Accessible endpoint for streamable connections.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add HSn0918/kubernetes-mcp/kubernetes-mcp-usage. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use kubernetes-mcp-usage immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

kubernetes-mcp-usage

Install kubernetes-mcp-usage, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Kubernetes MCP Usage Guide

When to Use

Use this skill when the user wants to operate Kubernetes through kubernetes-mcp:

  • connect MCP client to this server (stdio, sse, streamable);
  • discover resources, inspect cluster state, check logs/events/metrics;
  • troubleshoot failed tool calls and parameter mismatch.

Connection Checklist

  1. Confirm server is reachable:
    • stdio: binary command works with local kubeconfig.
    • streamable: endpoint is POST /mcp.
  2. Confirm Kubernetes auth is valid:
    • explicit --kubeconfig or in-cluster service account.
  3. Prefer smallest-scope query first:
    • namespace + kind filters before wide cluster scans.
  1. Health and inventory:
    • GET_CLUSTER_INFO
    • LIST_NAMESPACES
  2. Resource location:
    • SEARCH_RESOURCES (supports name=..., label=..., annotation=..., wildcard *)
    • LIST_K8S_RESOURCES
  3. Deep inspection:
    • GET_K8S_RESOURCE / DESCRIBE_K8S_RESOURCE
    • GET_EVENTS
  4. Runtime diagnosis:
    • GET_POD_LOGS
    • GET_POD_METRICS, GET_NODE_METRICS, GET_TOP_CONSUMERS

Practical Query Patterns

  • Find all pods in namespace:
    • SEARCH_RESOURCES {"kinds":"Pod","namespaces":"mcp-system","query":"name=*"}
  • Find by label wildcard:
    • SEARCH_RESOURCES {"query":"label=app:nginx-*","namespaces":"default"}
  • Find by annotation:
    • SEARCH_RESOURCES {"query":"annotation=team:platform","namespaces":"default"}
  • List known kind explicitly:
    • LIST_K8S_RESOURCES {"kind":"Pod","apiVersion":"v1","namespace":"default"}
  • List namespace resources by discovery:
    • LIST_K8S_RESOURCES {"namespace":"default"}

Error Handling Guidance

  • If listing fails with missing apiVersion:
    • provide both kind and apiVersion, or omit kind for discovery listing.
  • If search returns empty unexpectedly:
    • check kinds value (Pod/pods both accepted),
    • verify namespace scope,
    • test with query:"name=*" first.
  • If metrics tools fail:
    • confirm metrics-server is installed and accessible.

Safety

  • Avoid destructive actions (DELETE, large apply) unless user explicitly requests.
  • For changes, prefer VALIDATE_MANIFEST and DIFF_MANIFEST before APPLY_MANIFEST.

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