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An MCP server that lets AI assistants safely inspect and operate on Kubernetes clusters through natural conversation.
An MCP server that lets AI assistants safely inspect and operate on Kubernetes clusters through natural conversation.
An MCP server that lets AI assistants — Claude Desktop, Cursor, Claude Code — safely inspect and operate on Kubernetes clusters through natural conversation.
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 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.
| 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. |
--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.
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.
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-7d4f9crashing? Check its logs and recent events."
Ready-to-paste config snippets (read-only and writes-enabled variants) live in examples/ — see examples/README.md for setup notes.
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.
| 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 |
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.
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.
See docs/PROJECT_PLAN.md. Highlights for v2:
MIT — see LICENSE.
Built on top of:
Выполни в терминале:
claude mcp add k8s-mcp-server -- npx Безопасность
Низкий рискАвтоматическая эвристика по публичным данным — не гарантия безопасности.