Content
# k8s-mcp-go
**Safe, read-only-by-default Kubernetes access for AI agents.**
A Kubernetes MCP server that lets AI assistants inspect your cluster safely — without giving them unrestricted `kubectl`.
## What makes it different
- **Read-only by default**: useful for diagnosis without giving AI permission to mutate the cluster.
- **Explicit permission modes**: choose `readonly`, `readwrite`, or `dangerous` before the assistant starts.
- **No Docker required**: install via MCPB bundles or a single native binary.
- **Kubernetes-native visibility**: inspect pods, deployments, services, logs, events, nodes, and live CPU/memory usage.
- **Registry-ready distribution**: published as `io.github.kaneg/k8s-mcp-go` for MCP Registry consumers and packaged clients.
## Distribution
- [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers?search=io.github.kaneg/k8s-mcp-go): published as `io.github.kaneg/k8s-mcp-go`.
- [PulseMCP](https://www.pulsemcp.com/servers/kaneg-k8s-mcp-go): indexed from the MCP ecosystem with the official `server.json`.
- [Claude Code Marketplaces](https://claudemarketplaces.com/mcp/kaneg/k8s-mcp-go): listed with MCPB installation metadata.
## Why
Most AI agents can use Kubernetes tools.
The real problem is **how to stop them from changing the wrong thing**.
Giving an AI raw `kubectl` access is risky. Even a capable model can:
- delete the wrong resource
- restart the wrong workload
- apply a dangerous change
- turn a debugging session into a production incident
`k8s-mcp-go` gives AI agents a **guardrailed interface** to Kubernetes instead of unrestricted shell access.
It is built for the real-world question:
> How can I let AI help with Kubernetes, without letting it break my cluster?
## Permission Modes
You choose the boundary up front:
| What you want | Mode |
|---------------|------|
| "Let AI inspect and diagnose, but change nothing" | `readonly` |
| "Allow safe operational actions like scale and restart" | `readwrite` |
| "Give it full cluster power" | `dangerous` |
### `readonly` (default)
For diagnosis, inspection, and safe exploration.
AI can do things like:
- list pods, deployments, services, nodes, and namespaces
- read logs and events
- inspect cluster state
- check resource usage
It **cannot** modify workloads or delete resources.
### `readwrite`
For controlled operational workflows.
AI can do things like:
- scale deployments
- restart deployments
- restart statefulsets
- update images
- patch deployments
- create namespaces
It still cannot perform the most destructive operations.
### `dangerous`
Full access.
Use this only when you explicitly want AI to be able to:
- delete resources
- delete namespaces
- apply arbitrary YAML
If you are unsure, use `readonly`.
## Quick Start
### Option 1: MCPB Install (Recommended)
Download the `.mcpb` bundle for your platform from [Releases](https://github.com/kaneg/k8s-mcp-go/releases/latest). MCPB-compatible clients (Claude Desktop, Cursor, etc.) can install it directly — no Docker, no Go, no manual setup.
| OS | Arch | File |
|----|------|------|
| Linux | x86_64 | `k8s-mcp-go_*_linux_amd64.mcpb` |
| Linux | ARM64 | `k8s-mcp-go_*_linux_arm64.mcpb` |
| macOS | Intel | `k8s-mcp-go_*_darwin_amd64.mcpb` |
| macOS | Apple Silicon | `k8s-mcp-go_*_darwin_arm64.mcpb` |
| Windows | x86_64 | `k8s-mcp-go_*_windows_amd64.mcpb` |
| Windows | ARM64 | `k8s-mcp-go_*_windows_arm64.mcpb` |
### Option 2: Manual Binary Install
Grab the binary archive from [Releases](https://github.com/kaneg/k8s-mcp-go/releases/latest) and extract it:
```bash
# Example: Linux x86_64
tar xzf k8s-mcp-go_*_linux_amd64.tar.gz
chmod +x k8s-mcp-go
sudo mv k8s-mcp-go /usr/local/bin/
```
Then add it to your MCP client.
**Claude Desktop** (`claude_desktop_config.json`):
```json
{
"mcpServers": {
"k8s": {
"command": "k8s-mcp-go",
"args": ["-mode=readonly"]
}
}
}
```
**Cursor** (`.cursor/mcp.json`):
```json
{
"mcpServers": {
"k8s": {
"command": "k8s-mcp-go",
"args": ["-mode=readonly"]
}
}
}
```
Restart your client and start asking questions about your cluster.
## Example prompts
Once installed, ask your AI assistant things like:
- "Show me unhealthy pods in all namespaces."
- "Which pods are using the most memory?"
- "Summarize recent warning events."
- "Inspect this deployment and explain why it is not ready."
- "Check rollout status for this deployment."
In `readonly` mode, the assistant can investigate but cannot change the cluster.
## Why not just use kubectl?
Because the problem is not whether AI can talk to Kubernetes.
The problem is whether it can do so **safely**.
`kubectl` is powerful, but it does not give you a product-level permission mode for AI behavior.
With `k8s-mcp-go`, you decide whether the assistant can:
- inspect only
- perform limited operational actions
- or get full control
**The permission boundary is the product.**
## Available Tools (35 total)
Tools are grouped by permission level.
Names start with an action verb such as `get`, `list`, or `delete`; `top_nodes`
and `top_pods` retain Kubernetes' established `kubectl top` terminology.
### Readonly (24)
| Tool | Description |
|------|-------------|
| `get_server_info` | Show server version, mode, Kubernetes config source, and runtime details |
| `resolve_workload` | Resolve an app/workload name to matching resources and suggested next tools |
| `list_pods` | List pods; supports `all_namespaces=true` |
| `get_pod` | Get pod details |
| `get_pod_logs` | Get pod logs |
| `list_deployments` | List deployments; supports `all_namespaces=true` |
| `get_deployment` | Get deployment details |
| `list_statefulsets` | List StatefulSets; supports `all_namespaces=true` |
| `get_statefulset` | Get StatefulSet details |
| `list_services` | List services; supports `all_namespaces=true` |
| `get_service` | Get service details |
| `list_configmaps` | List ConfigMaps; supports `all_namespaces=true` |
| `get_configmap` | Get ConfigMap data |
| `list_secrets` | List Secrets (keys only); supports `all_namespaces=true` |
| `get_secret` | Get Secret metadata and keys |
| `list_pvc` | List PersistentVolumeClaims; supports `all_namespaces=true` |
| `list_ingress` | List Ingress resources; supports `all_namespaces=true` |
| `list_jobs` | List Jobs; supports `all_namespaces=true` |
| `top_nodes` | Current node CPU and memory usage |
| `top_pods` | Current pod CPU and memory usage |
| `list_nodes` | List cluster nodes |
| `list_namespaces` | List namespaces |
| `get_cluster_overview` | Cluster health summary |
| `list_events` | List events |
### Readwrite (7)
| Tool | Description |
|------|-------------|
| `scale_deployment` | Scale deployment replicas |
| `restart_deployment` | Rolling restart a deployment |
| `restart_statefulset` | Rolling restart a statefulset |
| `set_image` | Update container image |
| `get_rollout_status` | Check rollout progress |
| `create_namespace` | Create a new namespace |
| `patch_deployment` | Apply strategic merge patch |
### Dangerous (7)
| Tool | Description |
|------|-------------|
| `delete_pod` | Delete a pod |
| `delete_deployment` | Delete a deployment |
| `delete_statefulset` | Delete a StatefulSet and its pods |
| `delete_daemonset` | Delete a DaemonSet and its pods |
| `delete_resource` | Delete a resource without a dedicated delete tool |
| `delete_namespace` | Delete a namespace and all resources |
| `apply_yaml` | Apply arbitrary YAML manifest |
Prefer the dedicated delete tools above when one exists. Use `delete_resource`
as the fallback for other kinds. It resolves namespaced versus cluster-scoped
resources through Kubernetes discovery.
```json
{"api_version":"v1","kind":"ServiceAccount","namespace":"apps","name":"builder"}
{"api_version":"rbac.authorization.k8s.io/v1","kind":"ClusterRole","name":"auditor"}
```
## Kubernetes Configuration
Configuration is selected in this order:
1. The file specified by `KUBECONFIG`, when set.
2. The Pod's in-cluster ServiceAccount configuration.
3. `~/.kube/config` when running outside a cluster.
An explicit `KUBECONFIG` is authoritative. If it cannot be loaded, the server
returns an error instead of silently switching to the Pod's ServiceAccount.
In-cluster configuration uses Kubernetes' mounted token file so projected
ServiceAccount token rotation continues to work without copying tokens into a
kubeconfig.
## Environment Variables
| Variable | Description |
|----------|-------------|
| `KUBECONFIG` | Explicit kubeconfig path. When unset, use in-cluster configuration or fall back to `~/.kube/config`. |
## Build from Source
```bash
git clone https://github.com/kaneg/k8s-mcp-go.git
cd k8s-mcp-go
go build -o k8s-mcp-go .
```
## License
MIT
