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kubernetes-mcp-server
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kubernetes-mcp-server

Active·★ 2.2k·Apache-2.0·Updated 2026-10-13
★ Trending★ Essential

This is an MCP server implementation for Kubernetes and OpenShift. Its README lists automatic detection of changes in the kubeconfig (or in-cluster configuration), generic create, update, get, list and delete operations on any Kubernetes or OpenShift resource, and pod-specific operations such as listing, getting and deleting pods. The README is long (over 65k characters) and goes on to cover tools, configuration options, demos such as diagnosing and fixing an OpenShift deployment, and development notes.

The only requirement is access to a Kubernetes cluster. For Claude Desktop, VS Code and Cursor, the README gives an `npx` entry using `kubernetes-mcp-server@latest`, and Claude Code has a dedicated getting-started guide plus a separate guide for a locked-down, read-only ServiceAccount setup. The CLI can be run through `npx`, `uvx` or a downloaded release binary, and configuration is done with command-line arguments. It is published on npm and PyPI under the name `kubernetes-mcp-server` and is Apache-2.0 licensed.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-11.

License
Apache-2.0
Latest release
v0.0.67 · 2026-09-18
Last commit
2026-10-09
Contributors
77
Forks
453
Open issues and PRs
119
First published
2025-02-11
npm package
kubernetes-mcp-server 0.0.67 · 11,142 downloads last week
PyPI package
kubernetes-mcp-server 0.0.67 · 3,457 downloads last week

Source: GitHub, npm and PyPI public APIs.

#Kubernetes#OpenShift#MCP Server#Container Orchestration#Cloud Native#API Integration#Go#DevOps#AI Agent
$ Install
$ npx -y kubernetes-mcp-server@latest
↗ Visit site★ GitHub
01

Features

01Go-based native implementation: Directly interacts with Kubernetes API server, avoiding `kubectl`/`helm` wrapper overhead.
02Comprehensive resource management: Supports CRUD operations on any Kubernetes/OpenShift resource, including Pods, Namespaces, Events, Helm, and Tekton.
03Lightweight and Cross-Platform: Distributed as a single native binary for Linux, macOS, and Windows, also available as npm, Python, and Docker packages.
04Multi-Cluster support: Capable of interacting with multiple Kubernetes clusters simultaneously as defined in kubeconfig files.
05Configurable and Observability-ready: Supports CLI arguments, TOML config files, environment variables, and optional OpenTelemetry tracing/metrics.
02

Why choose it

+Works with any Kubernetes or OpenShift resource through generic CRUD, plus pod-specific tools
+Picks up kubeconfig changes automatically
+Runs from `npx`, `uvx` or a release binary, with ready-made config for Claude Desktop, VS Code and Cursor
+A documented read-only ServiceAccount setup for safer production use
03

Trade-offs

!Giving an AI client write access to a cluster is risky; use the read-only setup and review destructive actions before approving
!The README is very long, so finding the exact options takes time
!Requires working cluster access and sensible RBAC on your side
!Tool behavior depends on the model's choices; verify before running changes on production clusters
04

Compatibility

Go
Runtime
Verified via docs
Node.js
Runtime
Verified via docs
Python
Runtime
Verified via docs
Linux
OS
Verified via docs
macOS
OS
Verified via docs
Windows
OS
Verified via docs
05

Quick start

1
$ npx -y kubernetes-mcp-server@latest
06

Use cases

↳Integrate AI agents (e.g., Claude Desktop, VS Code, Cursor, Goose CLI) with Kubernetes for intelligent cluster management and automation.
↳Automate diagnosis and resolution of issues in OpenShift Deployments using AI-driven analysis and corrective actions.
↳Streamline application deployment and development workflows on Kubernetes/OpenShift with AI assistance, such as 'Vibe Coding' and GitHub Copilot integration.
↳Perform advanced Kubernetes operations like managing Helm releases, starting Tekton pipelines, and viewing detailed resource metrics through a unified MCP interface.
↳Enable secure and controlled access for AI tools to Kubernetes clusters by configuring read-only mode, denied resources, and specific toolsets.
07

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07Alternatives
Stats
GitHub Stars★ 2.2k
Last commit1d ago
StatusActive
LicenseApache-2.0
CategoryAPI Integration
Trend (30d)
+0k↑ 3.4%
Links
Documentation↗Discussion↗Issues↗Releases↗

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