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作者による説明(英語の原文)
Unified MCP server for Kubernetes, ArgoCD, Prometheus, PagerDuty, and Loki
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
KUBECONFIG, K8S_CONTEXT, ARGOCD_SERVER, ARGOCD_TOKEN, PROMETHEUS_URL, PROMETHEUS_BEARER_TOKEN, PAGERDUTY_TOKEN, PAGERDUTY_USER_EMAIL, LOKI_URL, LOKI_TOKEN「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"devops": {
"command": "npx",
"args": [
"-y",
"@notharshhaa/devops-mcp"
],
"env": {
"KUBECONFIG": "your-value",
"K8S_CONTEXT": "your-value",
"ARGOCD_SERVER": "your-value",
"ARGOCD_TOKEN": "your-value",
"PROMETHEUS_URL": "your-value",
"PROMETHEUS_BEARER_TOKEN": "your-value",
"PAGERDUTY_TOKEN": "your-value",
"PAGERDUTY_USER_EMAIL": "your-value",
"LOKI_URL": "your-value",
"LOKI_TOKEN": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add devops --env KUBECONFIG=your-value --env K8S_CONTEXT=your-value --env ARGOCD_SERVER=your-value --env ARGOCD_TOKEN=your-value --env PROMETHEUS_URL=your-value --env PROMETHEUS_BEARER_TOKEN=your-value --env PAGERDUTY_TOKEN=your-value --env PAGERDUTY_USER_EMAIL=your-value --env LOKI_URL=your-value --env LOKI_TOKEN=your-value -- npx -y @notharshhaa/devops-mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"devops": {
"command": "npx",
"args": [
"-y",
"@notharshhaa/devops-mcp"
],
"env": {
"KUBECONFIG": "your-value",
"K8S_CONTEXT": "your-value",
"ARGOCD_SERVER": "your-value",
"ARGOCD_TOKEN": "your-value",
"PROMETHEUS_URL": "your-value",
"PROMETHEUS_BEARER_TOKEN": "your-value",
"PAGERDUTY_TOKEN": "your-value",
"PAGERDUTY_USER_EMAIL": "your-value",
"LOKI_URL": "your-value",
"LOKI_TOKEN": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"devops": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@notharshhaa/devops-mcp"
],
"env": {
"KUBECONFIG": "your-value",
"K8S_CONTEXT": "your-value",
"ARGOCD_SERVER": "your-value",
"ARGOCD_TOKEN": "your-value",
"PROMETHEUS_URL": "your-value",
"PROMETHEUS_BEARER_TOKEN": "your-value",
"PAGERDUTY_TOKEN": "your-value",
"PAGERDUTY_USER_EMAIL": "your-value",
"LOKI_URL": "your-value",
"LOKI_TOKEN": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
KUBECONFIG envK8S_CONTEXT envARGOCD_SERVER envPROMETHEUS_URL envPAGERDUTY_USER_EMAIL envLOKI_URL envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント NotHarshhaa で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
入力が必要なもの:ARGOCD_TOKEN, PROMETHEUS_BEARER_TOKEN, PAGERDUTY_TOKEN, LOKI_TOKEN
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(2.1.1)がレジストリに届いたのは32 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:GitHub, Desktop Commander, Cloudflare MCP
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日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
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Unified MCP server for DevOps engineers — query and manage Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.
devops-mcp is an open source Model Context Protocol server that gives AI agents (Claude, etc.) real-time read and write access to your infrastructure stack — all from a single install.
Instead of copy-pasting kubectl output into a chat window, you can ask:
*"Why is the payments deployment in CrashLoopBackOff?"*
*"What changed in the last ArgoCD sync for the auth app?"*
*"Show me the p99 latency for the API gateway over the last hour."*
*"Who's on call right now and what incidents are open?"*
*"Debug the payments service - what's wrong with it?"*
...and get live answers, sourced directly from your cluster and tooling.
Providers included:
| Prefix | Provider | Transport |
|---|---|---|
k8s__* | Kubernetes (via kubeconfig or in-cluster SA) | client-go |
argo__* | ArgoCD | REST API |
prom__* | Prometheus | HTTP API (PromQL) |
pd__* | PagerDuty | REST API v2 |
helm__* | Helm | CLI (helm binary) |
devops__* | Cross-provider incident debugging | Aggregates all providers |
logs__* | Loki | HTTP API (LogQL) |
Add this to ~/.config/claude/claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": { "devops": { "command": "npx", "args": ["-y", "@notharshhaa/devops-mcp@latest"], "env": { "KUBECONFIG": "/home/you/.kube/config", "ARGOCD_SERVER": "https://argocd.company.com", "ARGOCD_TOKEN": "your-argocd-token", "PROMETHEUS_URL": "http://prometheus.monitoring:9090", "PAGERDUTY_TOKEN": "your-pd-api-token", "PAGERDUTY_USER_EMAIL": "you@company.com", "LOKI_URL": "http://loki.monitoring:3100", "LOKI_TOKEN": "your-loki-token" } } } }
Restart Claude Desktop. The devops server will appear in the tools list.
claude mcp add devops-mcp -e KUBECONFIG=$HOME/.kube/config \
-e ARGOCD_SERVER=https://argocd.company.com \ -e ARGOCD_TOKEN=... \ -e PROMETHEUS_URL=http://prometheus:9090 \ -e PAGERDUTY_TOKEN=... \ -e LOKI_URL=http://loki.monitoring:3100 \ -e LOKI_TOKEN=... \ -- npx -y @notharshhaa/devops-mcp@latest
Requires Node.js 20 or newer.
npx @notharshhaa/devops-mcp
git clone https://github.com/NotHarshhaa/devops-mcp cd devops-mcp npm install cp .env.example .env # fill in your values npm run dev
All config is via environment variables. Only set the ones for providers you actually use — providers with missing config are silently skipped.
# ── Kubernetes ────────────────────────────────────────────────
KUBECONFIG=/home/user/.kube/config # omit to use in-cluster service account K8S_CONTEXT=my-prod-context # optional: pin a specific context K8S_ALLOWED_NAMESPACES=default,backend # optional: restrict namespace access
ARGOCD_SERVER=https://argocd.company.com ARGOCD_TOKEN=eyJhbGci... # argocd account generate-token
PROMETHEUS_URL=http://prometheus:9090 PROMETHEUS_BEARER_TOKEN= # optional: for authenticated Prometheus
PAGERDUTY_TOKEN=your-api-v2-token PAGERDUTY_USER_EMAIL=you@company.com # required for PagerDuty incident mutations (From header)
LOKI_URL=http://loki.monitoring:3100 LOKI_TOKEN=your-loki-token
MCP_HTTP_HOST=127.0.0.1 # use 0.0.0.0 inside a container PORT=3000 MCP_AUTH_TOKEN=shared-secret # optional static Bearer token MCP_REQUEST_STATE_SECRET=32+-byte-secret # optional MRTR signing key shared by all replicas MCP_ALLOWED_HOSTS=localhost,127.0.0.1 # required with non-loopback binding MCP_ALLOWED_ORIGINS= # optional browser Origin hostname allowlist MCP_CACHE_TTL_MS=60000 # discovery/tools catalog TTL; 0 disables caching
DEVOPS_MCP_DRY_RUN=false # true = block all mutations globally DEVOPS_MCP_AUDIT_LOG=/var/log/devops-mcp-audit.jsonl
All tools follow a three-tier safety model:
dry_run: true; set dry_run: false to executeconfirm: true, or a 2026-07-28 client can complete the server's interactive MRTR confirmationk8s__*)| Tool | Tier | Description |
|---|---|---|
k8s__list_pods | read | List pods with status, restarts, node, age |
k8s__get_pod_logs | read | Tail or stream logs from a pod container |
k8s__describe_resource | read | Full describe for any resource type (pod, service, configmap, secret [values auto-redacted], deployment, statefulset, daemonset, job, cronjob) |
k8s__get_events | read | Cluster or namespace events, filterable by reason |
k8s__list_deployments | read | Deployments with replica counts, rollout health, and container images |
k8s__get_resource_usage | read | CPU/mem usage per pod via metrics-server |
k8s__get_node_status | read | Node health, conditions, capacity, allocatable resources, taints |
k8s__get_network_policies | read | Network policies with pod selectors and ingress/egress rules |
k8s__get_ingresses | read | Ingress resources with hosts, paths, backends, TLS config |
k8s__list_cronjobs | read | CronJobs with schedule, last run, active jobs, suspend status |
k8s__get_cronjob_status | read | Detailed CronJob status with recent job history |
k8s__diff_resource | read | Compare current resource state vs last-applied-configuration |
k8s__get_hpa | read | HorizontalPodAutoscaler with current/target metrics and scaling status |
k8s__list_pvcs | read | PersistentVolumeClaims with status, capacity, storage class |
k8s__list_services | read | Services with type, ports, selectors, clusterIP, endpoints |
k8s__list_contexts | read | All kubeconfig contexts and the active one |
k8s__switch_context | mutate | Preview a context selection; set K8S_CONTEXT and restart to apply it safely |
k8s__scale_deployment | mutate | Scale replicas with dry-run diff preview |
k8s__apply_manifest | mutate | Apply a manifest string with server-side dry-run |
k8s__rollout_restart | mutate | Trigger rolling restart of a deployment or statefulset |
k8s__delete_resource | destructive | Delete a named resource (pod, service, configmap, secret, deployment, statefulset, daemonset, job, cronjob) — requires direct or interactive confirmation |
argo__*)| Tool | Tier | Description |
|---|---|---|
argo__list_apps | read | All apps with health, sync status, source repo |
argo__get_app | read | Full spec and status for one application |
argo__get_app_diff | read | Live diff between git and cluster state |
argo__get_app_history | read | Deployment history with git SHAs and timestamps |
argo__get_resource_tree | read | Full owned resource tree for an app |
argo__sync_app | mutate | Trigger sync — supports dry-run, prune, force |
argo__rollback_app | mutate | Preview rollback to a history revision; set dry_run: false to execute |
argo__terminate_op | mutate | Preview cancellation of an in-progress sync; set dry_run: false to execute |
prom__*)| Tool | Tier | Description |
|---|---|---|
prom__query | read | Instant PromQL query with label + value output |
prom__query_range | read | Range query with step, returns time-series data |
prom__list_alerts | read | All alert rules with state (firing / pending / inactive) |
prom__get_firing_alerts | read | Only currently firing alerts with duration |
prom__list_targets | read | All scrape targets with health and last scrape |
prom__label_values | read | Enumerate values for a given label name |
prom__metric_metadata | read | Type, help text, and unit for a metric |
prom__compare_periods | read | 📈 Compare metrics between two time windows — detect before/after deployment changes |
prom__slo_status | read | 🎯 SLO compliance — error budget remaining, burn rate, time to exhaustion |
prom__summarize_service_health | read | 📊 Smart summary - human-readable service health metrics including latency changes, error rate vs SLO, and traffic patterns |
Example usage:
# Get a human-readable health summary
prom__summarize_service_health(service="payments", timeframeMinutes=30, sloThreshold=0.05)
What it outputs:
Why this matters: Instead of raw PromQL numbers that require interpretation, this tool provides actionable insights that AI agents can use directly in responses, making monitoring data actually useful for incident investigation and communication.
logs__*)| Tool | Tier | Description |
|---|---|---|
logs__get_recent_errors | read | Get recent error logs from Loki for debugging incidents |
logs__search | read | Search logs in Loki with custom query for root cause analysis |
Example usage:
# Get recent error logs
logs__get_recent_errors(service="payments", namespace="default", minutes=30, limit=50)
logs__search(query='{service="payments"} |= level="error"', limit=100)
Why this matters:
Output format:
This makes incident investigation complete by combining the "what" (metrics) with the "why" (logs).
pd__*)| Tool | Tier | Description |
|---|---|---|
pd__list_incidents | read | Open incidents with severity, status, assignee |
pd__get_incident | read | Full detail with alerts, notes, timeline |
pd__who_is_oncall | read | Current on-call per schedule or escalation policy |
pd__list_services | read | All services with integration keys and status |
pd__get_log_entries | read | Audit log for an incident (all state changes) |
pd__acknowledge_incident | mutate | Preview acknowledgement; set dry_run: false to execute |
pd__add_note | mutate | Preview appending a note; set dry_run: false to execute |
| pd__escalate_incident | destructive | Escalate to a different policy — requires direct or interactive confirmation
冒頭だけを表示しています。続きはリポジトリで読めます