GitHub
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作者提供的说明(英文原文)
Kubernetes MCP server with RBAC-style, context-scoped guardrails for AI agents.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"kubeleash": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}在终端中运行这条命令
claude mcp add kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"kubeleash": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"kubeleash": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/kubeleash/kubeleash:0.3.0"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 kubeleash 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.3.0)于5个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.