接入你的智能体
发布者自己的命令。不是 PlugMCP 端点。
用我们的密钥与日志托管一份副本。
npx -y [email protected]Claude Code 没有针对本地命令的安装链接。复制下方命令并在终端中运行。
KUBECONFIG=<value> MCP_TRANSPORT=<value> MCP_MODE=<value> MCP_CODE_MODE_DISABLED_TOOLS=<value> MCP_ARGO_TOOLS=<value> MCP_ARGOCD_TOOLS=<value> MCP_LOG_LEVEL=<value> MCP_KUBE_CONTEXT=<value> MCP_K8S_SKIP_TLS_VERIFY=<value> MCP_HIDE_SENSITIVE=<value> MCP_TIMEOUT=<value> MCP_HTTP_HOST=<value> MCP_HTTP_PORT=<value> MCP_HTTP_PATH=<value> MCP_HTTP_JSON_RESPONSE=<value> MCP_APPROVAL_STATE_SECRET=<secret> MCP_APPROVAL_REPLAY_DIR=<value> MCP_ALLOWED_HOSTS=<value> MCP_ALLOWED_ORIGINS=<value> KUBE_MCP_FORCE_VM_SANDBOX=<value> MCP_DISABLE_KUBERNETES_PLUGIN=<value> MCP_DISABLE_HELM_PLUGIN=<value> MCP_DISABLE_ARGO_PLUGIN=<value> MCP_DISABLE_ARGOCD_PLUGIN=<value> claude mcp add io.github.mikhae1-kubeview -- npx -y kubeview-mcp@2.3.0在终端中运行。
{ "mcpServers": { "io.github.mikhae1-kubeview": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "KUBECONFIG": "<value>", "MCP_TRANSPORT": "<value>", "MCP_MODE": "<value>", "MCP_CODE_MODE_DISABLED_TOOLS": "<value>", "MCP_ARGO_TOOLS": "<value>", "MCP_ARGOCD_TOOLS": "<value>", "MCP_LOG_LEVEL": "<value>", "MCP_KUBE_CONTEXT": "<value>", "MCP_K8S_SKIP_TLS_VERIFY": "<value>", "MCP_HIDE_SENSITIVE": "<value>", "MCP_TIMEOUT": "<value>", "MCP_HTTP_HOST": "<value>", "MCP_HTTP_PORT": "<value>", "MCP_HTTP_PATH": "<value>", "MCP_HTTP_JSON_RESPONSE": "<value>", "MCP_APPROVAL_STATE_SECRET": "<secret>", "MCP_APPROVAL_REPLAY_DIR": "<value>", "MCP_ALLOWED_HOSTS": "<value>", "MCP_ALLOWED_ORIGINS": "<value>", "KUBE_MCP_FORCE_VM_SANDBOX": "<value>", "MCP_DISABLE_KUBERNETES_PLUGIN": "<value>", "MCP_DISABLE_HELM_PLUGIN": "<value>", "MCP_DISABLE_ARGO_PLUGIN": "<value>", "MCP_DISABLE_ARGOCD_PLUGIN": "<value>" } } }}claude_desktop_config.json
远程 URL 还是本机命令？ 两种安装方式的区别
来自发布者
Read-only Model Context Protocol server for Kubernetes diagnostics. Instead of exposing dozens of tools, it gives the agent a sandboxed TypeScript runtime: a single call can query Kubernetes, Helm, Argo Workflows, and Argo CD, correlate the results, and return only the answer. Intermediate payloads never pass through the model's context window. Based on the pattern.
Read-only Model Context Protocol MCP server enabling code-driven AI analysis of Kubernetes clusters.
run_codev2 publishes exactly two public tools: run_code and an approval-gated kube_pod_exec. Everything else is discovered inside the sandbox via tools.list(), tools.search(), and tools.help(), following the MCP progressive discovery and programmatic calling guidance.
run_code executes bounded TypeScript with top-level await. One call can list workloads, correlate events, fetch logs, and diff Helm state without shipping intermediate payloads back through the model:
const pods = await tools.kubernetes.list({ namespace: 'payments' });
const unhealthy = pods.items.filter((p) => p.status?.phase !== 'Running');
return Promise.all(
unhealthy.map(async (pod) => ({
pod: pod.metadata?.name,
logs: await tools.kubernetes.logs({
namespace: 'payments',
podName: pod.metadata?.name,
tailLines: 100,
}),
})),
);
kube_pod_exec is unreachable from sandboxed code. Top-level exec requires MCP elicitation, is bound to the argument digest, expires after 10 minutes, and fails closed. kube_port_forward is never a top-level tool and is denied inside code mode by default. tools.disabled() reports which policy blocked a capability and whether that denial is configurable.helm binary is a fallback, not a prerequisite.Prerequisites: Node.js ≥ 22 and access to a cluster (KUBECONFIG or in-cluster service account).
npx -y kubeview-mcp
# Claude Code
claude mcp add kubernetes -- npx kubeview-mcp
{
"mcpServers": {
"kubeview": {
"command": "npx",
"args": ["-y", "kubeview-mcp"]
}
}
}
In Cursor, /kubeview/code-mode injects the typed API into context.
mkdir -p /tmp/kubeview-mcp-approvals
MCP_APPROVAL_STATE_SECRET='replace-with-at-least-32-random-bytes' \
MCP_APPROVAL_REPLAY_DIR=/tmp/kubeview-mcp-approvals \
MCP_TRANSPORT=http MCP_HTTP_HOST=127.0.0.1 MCP_HTTP_PORT=3000 npx -y kubeview-mcp
Endpoint: http://127.0.0.1:3000/mcp. HTTP follows the MCP 2026-07-28 stateless core: a fresh server per request, no initialize, no Mcp-Session-Id. Each request carries protocol version, client identity, and capabilities in _meta; modern requests add Mcp-Method/Mcp-Name for gateway routing. 2025-era clients use the SDK's stateless fallback on the same endpoint. State that must survive across calls has to be passed as tool arguments or handles.
HTTP mode refuses to start without both approval variables. Multi-replica deployments need the same secret and a shared writable replay directory; the /tmp example is for a single process only. The published MCP registry entry still targets stdio.
Domain tools use an operation discriminator:
helm — list | get | debugargo — list | get | logs | cron_list (when Workflow or CronWorkflow is discoverable)argocd — list | get | resources | logs | history | status (when Application is discoverable, or with ARGOCD_SERVER + ARGOCD_AUTH_TOKEN)Discovery is cached per kube context for 60 s. Missing optional APIs are omitted, not fatal. argo and argocd are registered when the API exists in the default context or in any exact context name listed in MCP_KUBE_CONTEXTS.
Every cluster tool accepts an optional context argument (a kubeconfig context name or an MCP_KUBE_CONTEXTS alias); kube_contexts lists the contexts you can target. Without it, calls behave as before: MCP_KUBE_CONTEXT, then the kubeconfig current-context. Context is per call rather than per session, which keeps HTTP mode stateless and lets one script query several clusters concurrently.
MCP_KUBE_CONTEXTS is a comma-separated list. Plain entries are context names with optional * wildcards; alias=context entries map a short name to a real context. Once set, only matching contexts, alias targets, and MCP_KUBE_CONTEXT are reachable, including for Helm/Argo/Argo CD CLI fallbacks, which receive --kube-context/--context for the resolved context. Add * to keep every context while defining aliases.
MCP_KUBE_CONTEXT=dev \
MCP_KUBE_CONTEXTS='dev,staging-*,prod=arn:aws:eks:eu-west-1:123456789012:cluster/prod' \
npx -y kubeview-mcp
In run_code, set a default for the whole script with the context argument, or scope it with tools.withContext(); a per-call context always wins:
const staging = tools.withContext('staging-eu');
const [stagingApi, prodApi] = await Promise.all([
staging.kubernetes.diagnose({ resourceType: 'deployment', name: 'api', namespace: 'shop' }),
tools.kubernetes.diagnose({ resourceType: 'deployment', name: 'api', namespace: 'shop', context: 'prod' }),
]);
return { staging: stagingApi.summary, prod: prodApi.summary };
kube_pod_exec resolves the context before asking for approval; the approval prompt names it, and the approval is bound to it.
Code mode is the default (MCP_MODE=code). The agent writes short TypeScript against a typed tools global instead of calling dozens of MCP tools.
Inside run_code:
tools namespaces for Kubernetes, Helm, and any detected Argo capabilities, generated from live schemas so parameters cannot be hallucinated.tools.list(), tools.search(), tools.help(), and tools.disabled() (the last reports why a capability was blocked).tools.kubernetes.contexts(), tools.withContext(name), and per-call context arguments (see Multiple clusters).console and tools in scope — no filesystem, no network, no process.Pod exec approval uses MCP elicitation and fails closed. The standalone npm run code-mode launcher has no trusted approval UI, so it always denies pod exec.
Diagnose Pods, Deployments, StatefulSets, DaemonSets, ReplicaSets, Jobs, and CronJobs in one code-mode call:
return await tools.kubernetes.diagnose({
resourceType: 'deployment',
name: 'payments-api',
namespace: 'payments',
includeLogs: true,
});
Resource types default to pod and accept case-insensitive singular or plural names. Namespace defaults to the current context, then default. Diagnosis follows controller ownership by UID and correlates status, events, required configuration keys, image-pull Secrets, PVCs, and failing-container logs. Configuration and Secret values are never returned. Log and event text honor MCP_HIDE_SENSITIVE.
To diagnose a Pod from the CLI:
npm run command -- kube_diagnose --name monitor-eks-aid-847484f765-4hwzz
For controllers, add --resourceType deployment (or another supported type). Add --namespace when the workload is outside the current namespace.
Results contain target, context, observedAt, health, summary, findings, evidence, and coverage. Findings reference evidence and distinguish historical failures from current problems; possible causes are separate from observed facts. Missing optional configuration is expected. Forbidden, unavailable, or missing required reads remain visible in coverage.errors; truncation and skipped reads appear in coverage.truncations. Health is healthy, degraded, or unknown; a confirmed failure can be reported even when collection is incomplete.
MCP_CODE_MODE_DISABLED_TOOLS (comma-separated) controls which capabilities are blocked inside run_code. Resolution order:
MCP_CODE_MODE_DISABLED_TOOLS env vardisabledTools in kube-mcp.code-mode.json["kube_port_forward"]An empty env value clears the list. kube_pod_exec cannot be added — it is permanently blocked.
MCP 2026-07-28:
structuredContent with text fallbackread-only, destructive, idempotent, open-world annotationsMcp-Method, Mcp-Name)git clone https://github.com/mikhae1/kubeview-mcp.git
cd kubeview-mcp && npm install
npm run build # compile
npm start # build + run
npm test # jest suite
npm run typecheck # tsc --noEmit
# Invoke a tool directly
npm run command -- kube_list --namespace=default
Protocol tests pin the SDK v2 client to 2026-07-28 and route through the server handler in-process (no open ports):
npm test -- --runInBand \
tests/server/StreamableHttpTransport.integration.test.ts \
tests/server/StreamableHttpRuntime.test.ts \
tests/server/TransportConfig.test.ts \
tests/compat/McpSdkCompatibility.test.ts
Contributions are welcome! Please feel free to submit an issue or a pull request.
MIT © mikhae1
Read-only Model Context Protocol MCP server enabling code-driven AI analysis of Kubernetes clusters.
{ "mcpServers": { "io.github.mikhae1-kubeview": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "KUBECONFIG": "<value>", "MCP_TRANSPORT": "<value>", "MCP_MODE": "<value>", "MCP_CODE_MODE_DISABLED_TOOLS": "<value>", "MCP_ARGO_TOOLS": "<value>", "MCP_ARGOCD_TOOLS": "<value>", "MCP_LOG_LEVEL": "<value>", "MCP_KUBE_CONTEXT": "<value>", "MCP_K8S_SKIP_TLS_VERIFY": "<value>", "MCP_HIDE_SENSITIVE": "<value>", "MCP_TIMEOUT": "<value>", "MCP_HTTP_HOST": "<value>", "MCP_HTTP_PORT": "<value>", "MCP_HTTP_PATH": "<value>", "MCP_HTTP_JSON_RESPONSE": "<value>", "MCP_APPROVAL_STATE_SECRET": "<secret>", "MCP_APPROVAL_REPLAY_DIR": "<value>", "MCP_ALLOWED_HOSTS": "<value>", "MCP_ALLOWED_ORIGINS": "<value>", "KUBE_MCP_FORCE_VM_SANDBOX": "<value>", "MCP_DISABLE_KUBERNETES_PLUGIN": "<value>", "MCP_DISABLE_HELM_PLUGIN": "<value>", "MCP_DISABLE_ARGO_PLUGIN": "<value>", "MCP_DISABLE_ARGOCD_PLUGIN": "<value>" } } }}工具
暂无工具列表。远程服务器在首次健康检查后会获得工具列表。
常见问题
在本页复制适用于 Cursor、Claude Desktop、Claude Code 或 VS Code 的 stdio 配置。它使用发布者的安装方式，而不是 PlugMCP 代理。
发布者列出了以下环境变量：KUBECONFIG, MCP_TRANSPORT, MCP_MODE, MCP_CODE_MODE_DISABLED_TOOLS, MCP_ARGO_TOOLS, MCP_ARGOCD_TOOLS, MCP_LOG_LEVEL, MCP_KUBE_CONTEXT, MCP_K8S_SKIP_TLS_VERIFY, MCP_HIDE_SENSITIVE, MCP_TIMEOUT, MCP_HTTP_HOST, MCP_HTTP_PORT, MCP_HTTP_PATH, MCP_HTTP_JSON_RESPONSE, MCP_APPROVAL_STATE_SECRET, MCP_APPROVAL_REPLAY_DIR, MCP_ALLOWED_HOSTS, MCP_ALLOWED_ORIGINS, KUBE_MCP_FORCE_VM_SANDBOX, MCP_DISABLE_KUBERNETES_PLUGIN, MCP_DISABLE_HELM_PLUGIN, MCP_DISABLE_ARGO_PLUGIN, MCP_DISABLE_ARGOCD_PLUGIN。
Kubeview 通过 stdio 在本地运行。
上次检查时间：2026-11-09。 Read-only Model Context Protocol MCP server enabling code-driven AI analysis of Kubernetes clusters.