REA
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Kubernetes MCP server with RBAC-style, context-scoped guardrails for AI agents.
Pick the AI app you use, then copy the settings.
Passed 3/3 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Docker on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Docker
SettingsDeveloperEdit Config
{
"mcpServers": {
"kubeleash": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}Use Kubeleash and tell me what you can do for me, then show me one thing✓ If Claude says it is using Kubeleash or shows a Kubeleash tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Kubeleash yet
Kubeleash runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Kubeleash
B · Others in Developer tools that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add --scope user kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0You should see Kubeleash listed as connected
Use Kubeleash and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Kubeleash or shows a Kubeleash tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Use Kubeleash and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Kubeleash or shows a Kubeleash tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Use Kubeleash and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Kubeleash or shows a Kubeleash tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.
JSON settings are under “For developers” below
Claude Code
claude mcp add --scope user kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"kubeleash": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"kubeleash": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"kubeleash": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
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 12, 2026
The registry name was verified with the GitHub account kubeleash, which owns the repo
Code last changed 6 months ago
Uses Apache-2.0
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
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Posts here are written by users, not the PopNx team.
No reviews yet
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed 6 months ago, and the latest version (0.3.0) reached the registry 6 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: REA, GitHub, Serena MCP: the IDE for your agent
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
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.
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).
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:
kubeconfig-grants ∩ policy-allows — kubeleash only ever *subtracts*.delete/exec/…) as a safety net against agent mistakes and prompt injection.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.
policies:
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).
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
curl -fsSL https://raw.githubusercontent.com/kubeleash/kubeleash/main/examples/policy.yaml -o policy.yaml
kubeleash --policy policy.yaml --print-effective-policy
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. |
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.
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
# Homebrew
brew install kubeleash/tap/kubeleash
go install github.com/kubeleash/kubeleash/cmd/kubeleash@latest
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.
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" } } } }
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.