k8s-readonly-mcp
A read-only MCP server for inspecting Kubernetes clusters, allowing LLMs to list resources, describe pods, and read logs without mutation.
README
k8s-readonly-mcp
A read-only Model Context Protocol (MCP) server that lets an LLM inspect a Kubernetes cluster — list pods, read logs, describe resources — but never mutate it.
Why I built it
I spend a lot of time embedded in customer Kubernetes environments. The most common thing I want from an LLM is "help me understand what's happening in this cluster" — without ever giving it the ability to change anything. So I built the safety in structurally rather than trusting the model to behave.
Every tool call routes through a single function that checks the kubectl verb against an
allow-list of read-only verbs (get, describe, logs, top, …). There is no code path that
can apply, delete, scale, or exec. If the model asks for a mutation, the server refuses.
This is the same least-privilege, human-in-the-loop instinct that any production agent needs.
What it does
| Tool | Description |
|---|---|
list_namespaces |
List all namespaces |
list_pods |
List pods in a namespace (or all namespaces) |
describe_pod |
Full status, events, and config for one pod |
get_pod_logs |
Last N lines of a pod's logs |
list_deployments |
Deployments and their ready/up-to-date status |
Quick start
# 1. Install (using uv — https://docs.astral.sh/uv/)
uv sync
# 2. Make sure kubectl points at a cluster.
# A local cluster is perfect for trying this safely:
# kind create cluster (or: minikube start)
kubectl get nodes
# 3. Run the server
uv run k8s-readonly-mcp
Connect it to Claude Desktop
Add this to your Claude Desktop MCP config
(~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"k8s-readonly": {
"command": "uv",
"args": ["--directory", "/absolute/path/to/k8s-readonly-mcp", "run", "k8s-readonly-mcp"]
}
}
}
Then ask Claude things like "What pods are failing in the default namespace, and why?" — it will
call list_pods and describe_pod, reason over the output, and explain — but it physically cannot
change your cluster.
Design decisions
- Allow-list, not block-list. I enumerate what's permitted rather than trying to block bad verbs. A block-list is one forgotten verb away from a mutation; an allow-list fails closed.
- One chokepoint. All
kubectlexecution goes through_run_kubectl. The security boundary is one function you can audit in 30 seconds. - Timeouts and clear errors. Calls time out and surface
kubectl's stderr instead of hanging or failing silently — the model gets actionable feedback.
What I'd do next
- Add resource-level scoping (restrict to specific namespaces per connection).
- Stream large log outputs instead of buffering.
- Add a small eval that checks the server refuses every mutating verb.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.