Kubeleash

Name: Kubeleash
Author: kubeleash

by kubeleashversion 0.3.0i★ –iRuns on your computer

Registry nameio.github.kubeleash/kubeleash

Install

Overview

Description from the maker (original English)

Kubernetes MCP server with RBAC-style, context-scoped guardrails for AI agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "kubeleash": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kubeleash/kubeleash:0.3.0"
      ]
    }
  }
}

Run this in your terminal

claude mcp add kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "kubeleash": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kubeleash/kubeleash:0.3.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "kubeleash": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kubeleash/kubeleash:0.3.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account kubeleash, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

More stars than 0% of the other 1393 servers in this category
Published to the registry more recently than 23% of the other 1393 servers in this category
Basic checks equal to or better than 100% of the other 1393 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Kubeleash safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

kubeleash Point it at your over-privileged kubeconfig — it still can't nuke prod.

Guardrails for AI agents on your cluster. kubeleash is a local MCP server for Kubernetes whose differentiator is RBAC-style, *context-scoped* access control. Point it at a kubeconfig — even a cluster-admin one — and a local policy file constrains what the agent can actually do, per kube context, with destructive actions gated before any call reaches the cluster.

Add kubeleash to your AI client

Install launches the local kubeleash binary — get it via brew , go install , or the container (see Install ). VS Code installs in one click; Cursor & Claude open the setup steps (GitHub strips the cursor:// one-click link, so it lives there as copy-paste).

Why

Most Kubernetes MCP servers inherit the kubeconfig's permissions wholesale — whatever the credentials grant, the agent can do. kubeleash adds three things native RBAC can't express for this use case:

Constrain the agent independently of the credentials. Effective access is always kubeconfig-grants ∩ policy-allows — kubeleash only ever *subtracts*.
Context-aware guardrails. Policy varies by context (prod vs staging vs dev); native RBAC is per-cluster.
Block destructive verbs (delete/exec/…) as a safety net against agent mistakes and prompt injection.

What kubeleash enforces

kubeleash governs only the calls routed through it. It provides a hard guarantee when it is the agent's *sole* path to the cluster. An agent that also has shell access (raw kubectl, oc, the API) can step around it, so in a shell-enabled assistant kubeleash is advisory — pair it with the using-kubeleash skill, which instructs the agent to stop (not reach for kubectl) when the leash is unavailable.

Policy in 10 seconds

policies:

contexts: ".*prod.*" # regex over the active context name allow: resources: ["*"] verbs: [get, list, watch] # read-only in prod deny: verbs: [exec] # never, regardless of credentials

Deny wins. Default deny. A broken policy refuses to start — it never fails open.

See examples/policy.yaml for a fuller, commented policy (read-only prod, broader staging, namespace-scoped dev).

Quickstart

Install it (Homebrew shown — see Install for go install and the container), then exercise a policy without touching any cluster:

brew install kubeleash/tap/kubeleash

Grab the commented example policy:

curl -fsSL https://raw.githubusercontent.com/kubeleash/kubeleash/main/examples/policy.yaml -o policy.yaml

See how kubeleash validates and normalizes a policy (no cluster needed):

kubeleash --policy policy.yaml --print-effective-policy

Try it without touching any cluster — every decision is logged, nothing runs:

kubeleash --policy policy.yaml --dry-run

Prefer source? git clone https://github.com/kubeleash/kubeleash && cd kubeleash && go build -o kubeleash ./cmd/kubeleash (Go 1.26+).

Then point an MCP client at it (see below). kubeleash speaks MCP over stdio, so it's launched by your client, not run as a daemon.

Flag	Purpose
`--policy`	Policy file. Required (or set `K8S_MCP_POLICY`); with neither, kubeleash refuses to start — default-deny never fails open.
`--kubeconfig`	Explicit kubeconfig. Omit to use the standard client-go rules (`$KUBECONFIG`, `~/.kube/config`).
`--dry-run`	Evaluate + log every decision, but never execute against a cluster.
`--print-effective-policy`	Print the resolved/normalized rules and exit.
`--log-level`	`debug` / `info` / `warn` / `error` (default `info`). The audit log is JSON on stderr (stdout is the MCP transport).
`--version`	Print version, commit, and build date.

Install

All channels run kubeleash locally over stdio — your client launches the binary; nothing is hosted. kubeleash is listed in the official MCP Registry as io.github.kubeleash/kubeleash, so registry-aware clients can discover it too.

One-click

The Add to Cursor / VS Code buttons at the top are the fastest path (they need the kubeleash binary on PATH — see Manual). Other clients:

Claude Code — this repo is its own plugin marketplace:

/plugin marketplace add kubeleash/kubeleash

/plugin install kubeleash@kubeleash

No separate install step: on first run the plugin uses a kubeleash already on your PATH, or otherwise downloads the matching release binary (verifying its checksum) and caches it.

Safe by default — no policy authoring required first: if you have no policy at ~/.kubeleash/policy.yaml, the plugin writes a read-only starter there on first run (allow get/list/watch, deny exec/delete). Review and widen it to grant more access. (This convenience is the plugin's only; the raw binary still requires an explicit --policy and refuses to start without one.)

The plugin also ships two skills — using-kubeleash (how an agent should query and act through the gated tools) and authoring-kubeleash-policy (how to write the policy) — so the agent understands the guardrails, not just the tool list.

Claude Desktop — download kubeleash.mcpb from the releases page and double-click it; the bundle ships the binary and prompts you for the policy and kubeconfig.

Raw Cursor / VS Code deeplink URLs (if a button doesn't fire)

Cursor (can't prompt — edit the placeholder path afterward in *Settings → MCP*). Decodes to {"command":"kubeleash","args":["--policy","/absolute/path/to/policy.yaml"]}:

cursor://anysphere.cursor-deeplink/mcp/install?name=kubeleash&config=eyJjb21tYW5kIjoia3ViZWxlYXNoIiwiYXJncyI6WyItLXBvbGljeSIsIi9hYnNvbHV0ZS9wYXRoL3RvL3BvbGljeS55YW1sIl19

VS Code (prompts for the policy path):

vscode:mcp/install?%7B%22name%22%3A%22kubeleash%22%2C%22command%22%3A%22kubeleash%22%2C%22args%22%3A%5B%22--policy%22%2C%22%24%7Binput%3ApolicyPath%7D%22%5D%2C%22inputs%22%3A%5B%7B%22id%22%3A%22policyPath%22%2C%22type%22%3A%22promptString%22%2C%22description%22%3A%22Path%20to%20your%20kubeleash%20policy.yaml%22%7D%5D%7D

Manual

# Homebrew

brew install kubeleash/tap/kubeleash

Go

go install github.com/kubeleash/kubeleash/cmd/kubeleash@latest

Container (great for running the MCP server sandboxed)

docker run --rm -i -v ~/.kube:/root/.kube:ro -v ./policy.yaml:/policy.yaml:ro \ ghcr.io/kubeleash/kubeleash --policy /policy.yaml

kubeleash runs locally over stdio and talks only to your clusters. There

is intentionally no remote/hosted URL connector — it would mean handing

your cluster credentials to a third party.

Use it as an MCP server

kubeleash exposes 8 generic, GVK-agnostic tools (k8s_list, k8s_get, k8s_apply, k8s_delete, k8s_logs, k8s_exec, k8s_scale, and k8s_capabilities) that work for any resource, including CRDs. Every call is checked against your policy and recorded to a JSON audit log on stderr (stdout is the MCP transport). It speaks MCP over stdio — point your client at the binary (or container):

// Claude Desktop / Cursor / VS Code MCP config

{ "mcpServers": { "kubeleash": { "command": "kubeleash", "args": ["--policy", "/absolute/path/to/policy.yaml"], "env": { "KUBECONFIG": "/absolute/path/to/kubeconfig" } } } }

Privacy

Zero telemetry. No phone-home. Local-only by design. kubeleash talks only to the Kubernetes API servers you point it at — there is intentionally no remote or hosted connector to route your cluster credentials through. That's a feature, not a gap: you run it against real clusters with privileged credentials, so nothing should sit between the agent and your API server but the leash.

Project

Design · Contributing · Security & threat model · Code of Conduct
License: Apache-2.0

Kubeleash

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Add kubeleash to your AI client

Why

What kubeleash enforces

Policy in 10 seconds

Quickstart

Grab the commented example policy:

See how kubeleash validates and normalizes a policy (no cluster needed):

Try it without touching any cluster — every decision is logged, nothing runs:

Install

One-click

Manual

Go

Container (great for running the MCP server sandboxed)

Use it as an MCP server

Privacy

Project