Kubeleash
What it does
Kubernetes MCP server with RBAC-style, context-scoped guardrails for AI agents.
- Connects 在你的电脑上运行
- Account or key No key needed
- Category 开发者工具
安装
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行 · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要先在电脑上安装 Docker(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
打开电脑版 Claude 应用的设置文件
SettingsDeveloperEdit Config
粘贴这些设置并保存文件
{ "mcpServers": { "kubeleash": { "command": "docker", "args": [ "run", "-i", "--rm", "ghcr.io/kubeleash/kubeleash:0.3.0" ] } } }退出 Claude 再重新打开
试一试
用 Kubeleash 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Kubeleash,或回答中出现 Kubeleash 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Kubeleash
Kubeleash 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Kubeleash 的应用
- 需要先在电脑上安装 Docker(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
- 需要先在电脑上安装 Docker(只需一次)
- 需要先在电脑上安装 Docker(只需一次)
- 需要先在电脑上安装 Docker(只需一次)
B · 开发者工具 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Sentry✓ ChatGPT
- Compiler Explorer✓ ChatGPT
- GitDiagram✓ ChatGPT
可连接 Claude Code,但需要先准备
需要先在电脑上安装 Docker(只需一次)
打开终端
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
粘贴这条命令并按 Enter
claude mcp add --scope user kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0在 Claude Code 中输入 /mcp
应能看到 Kubeleash 在列表中并显示已连接
试一试
用 Kubeleash 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Kubeleash,或回答中出现 Kubeleash 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要先在电脑上安装 Docker(只需一次)
在 Cursor 中以 Agent 模式打开 AI 聊天
试一试
用 Kubeleash 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Kubeleash,或回答中出现 Kubeleash 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要先在电脑上安装 Docker(只需一次)
在 VS Code 中以 Agent 模式打开 AI 聊天
试一试
用 Kubeleash 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Kubeleash,或回答中出现 Kubeleash 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
开发者专用:终端命令和 JSON 设置
安装在电脑上
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"
]
}
}
}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。
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
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。
基础检查i
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14日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 kubeleash 验证,该账户拥有此仓库
- ✓ 通过
仍在维护
代码最后更新于6个月前
- ✓ 通过
有许可证
使用 Apache-2.0
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
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
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5889 个服务器的 69%
- 发布到注册中心的时间比此分类中其他 5889 个服务器的 14% 更新
- 基础检查结果等于或优于此分类中其他 5889 个服务器的 100%
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。
常见问题
Kubeleash 安全吗?
它在 3 项适用的基础检查中通过了 3 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。
它需要哪些密钥或代码?
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。
它在我的电脑上运行还是在云端?
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)。
它还在维护吗?
GitHub 仓库最后更新于6个月前,最新版本(0.3.0)于6个月前进入注册中心。
哪些应用可以使用它?
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。
有什么可以替代它?
同一分类中有:REA, GitHub, Serena MCP: the IDE for your agent
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Serena MCP: the IDE for your agent
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
作者的 README
打开 README
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.
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