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k8s-mcp-server

An MCP server that lets AI assistants — Claude Desktop, Cursor, Claude Code — safely inspect and operate on Kubernetes clusters through natural conversation.

CI Python 3.13+ License: MIT MCP PyPI

What it does

k8s-mcp-server gives Claude (and any other MCP-compatible AI assistant) safe, read-only access to Kubernetes clusters by default — list pods, tail logs, inspect deployments, view metrics, and describe any resource through natural conversation. Optional write operations (scale, restart, delete) live behind an --enable-writes flag and default to dry-run, so the LLM can't accidentally change cluster state.

Built with 528 unit tests against mocked K8s APIs plus a kind-cluster integration smoke test on every CI run — 100% library coverage.

Demo

Demo coming: a 30-second loop of Claude Desktop diagnosing a crashing pod — the model calls list_pods, spots CrashLoopBackOff, fetches get_pod_logs with previous=True, reads the stack trace, and suggests the fix.

Features

Read operations (13 tools)

Tool

What it does

list_namespaces

List all namespaces with status and age.

list_pods

List pods, filterable by namespace, labels, or field selectors.

get_pod

Single pod's full state — container statuses, conditions, recent events.

get_pod_logs

Pod logs with tail_lines, since_seconds, and previous (post-crash).

list_deployments

List deployments with replica counts and primary container image.

get_deployment

Full deployment state plus the last 5 ReplicaSets (rollout history).

list_services

List services with ports and LoadBalancer external IPs.

list_nodes

List nodes with health, roles, kubelet version, capacity.

get_node

Full node detail with conditions, taints, and pods-on-node count.

list_events

Cluster events filtered by kind/name/type/since, most recent first.

describe_resource

Structured describe view across 7 kinds (Secret values redacted).

top_pods

Pod CPU/memory usage (requires metrics-server).

top_nodes

Node CPU/memory usage with percent against allocatable.

Write operations (3 tools — require --enable-writes)

Tool

What it does

scale_deployment

Set the replica count of a deployment via the /scale sub-resource.

restart_deployment

Trigger a rollout restart (kubectl-compatible annotation).

delete_pod

Delete a pod, optionally with force=True for immediate kill.

Every write tool defaults to dry_run=True. Full input/output specs in docs/TOOLS_SPEC.md.

Installation

Option A — try without installing (recommended for first run):

uvx --from kubernetes-mcp k8s-mcp-server --help

Option B — install for daily use:

pip install kubernetes-mcp

You'll need a working ~/.kube/config pointing at the cluster you want to inspect.

Quick Start (Claude Desktop)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "kubernetes": {
      "command": "uvx",
      "args": ["k8s-mcp-server"]
    }
  }
}

Restart Claude Desktop. You should now be able to ask:

"List all pods in the staging namespace that aren't running."

"Why is pod api-7d4f9 crashing? Check its logs and recent events."

Examples

Ready-to-paste config snippets (read-only and writes-enabled variants) live in examples/ — see examples/README.md for setup notes.

Security Model

All write operations are off by default. The --enable-writes flag at server start is required to register them at all (Layer 1 + 2 of defense-in-depth). Once enabled, every write tool re-checks the flag at handler entry (Layer 3) and defaults to dry_run=True (Layer 4) — the LLM must explicitly pass dry_run=False to apply. The optional --namespaces dev,staging allowlist limits the blast radius for both reads and writes regardless of the flag. Every write attempt is audited at INFO level on the k8s_mcp_server.audit logger with the tool name, target, dry_run value, and tool-specific deltas (Layer 5).

Secret values are never returned — even via describe_resource(kind="secret"), only key names surface. The kubectl.kubernetes.io/last-applied-configuration annotation is stripped from Secret responses to prevent annotation-based leaks.

Read docs/SECURITY.md for the full threat model and the layered defense table.

Configuration

Flag

Default

Description

--enable-writes

off

Register write tools

--namespaces ns1,ns2

all

Restrict to specific namespaces

--kubeconfig PATH

~/.kube/config

Override kubeconfig path

--context NAME

current

Override kubeconfig context

--log-level LEVEL

INFO

DEBUG / INFO / WARNING / ERROR

Architecture

Tools are registered via a small dataclass-based registry; each tool is a single async function that returns a structured ToolResult(success, data, error, audit) envelope and never raises into the MCP layer. Read tools defer to a shared namespace allowlist resolver (resolve_read_namespaces) and per-kind formatters in tools/. Write tools follow a strict three-layer defense pattern (CLI flag → server-level registry filter → in-handler assert_writes_enabled) on top of dry-run-by-default and audit logging. The polymorphic describe_resource tool dispatches via a per-kind table covering pod / deployment / service / node / configmap / secret / ingress.

See CLAUDE.md §6.1 for the Write Tool Contract.

Development

git clone https://github.com/sarah-salah/k8s-mcp-server
cd k8s-mcp-server
uv sync
uv run pytest
uv run ruff check
uv run mypy src/

Project conventions and workflow in CLAUDE.md. Integration tests against a real kind cluster are documented in docs/INTEGRATION_TESTING.md.

Roadmap (v2)

See docs/PROJECT_PLAN.md. Highlights for v2:

  • HTTP / SSE transport

  • In-cluster deployment with Helm chart

  • ServiceAccount + RBAC

  • Persistent audit log

License & Acknowledgments

MIT — see LICENSE.

Built on top of:

A
license - permissive license
-
quality - not tested
C
maintenance

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