devops MCP server

devops-mcp

Unified MCP server for DevOps engineers — query and manage Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.

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What is this?

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)

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Quick start

Claude Desktop (stdio — recommended)

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 Code (CLI)

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

Local dev / test

Requires Node.js 20 or newer.

npx @notharshhaa/devops-mcp
# or clone and run:
git clone https://github.com/NotHarshhaa/devops-mcp
cd devops-mcp
npm install
cp .env.example .env   # fill in your values
npm run dev

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Configuration

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 ───────────────────────────────────────────────────
ARGOCD_SERVER=https://argocd.company.com
ARGOCD_TOKEN=eyJhbGci...                 # argocd account generate-token

# ── Prometheus ───────────────────────────────────────────────
PROMETHEUS_URL=http://prometheus:9090
PROMETHEUS_BEARER_TOKEN=                 # optional: for authenticated Prometheus

# ── PagerDuty ────────────────────────────────────────────────
PAGERDUTY_TOKEN=your-api-v2-token
PAGERDUTY_USER_EMAIL=you@company.com     # required for PagerDuty incident mutations (From header)

# ── Loki ───────────────────────────────────────────────────
LOKI_URL=http://loki.monitoring:3100
LOKI_TOKEN=your-loki-token

# ── Stateless Streamable HTTP ────────────────────────────────
# For stdio mode (default): no transport config needed
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

# ── Safety ───────────────────────────────────────────────────
DEVOPS_MCP_DRY_RUN=false                # true = block all mutations globally
DEVOPS_MCP_AUDIT_LOG=/var/log/devops-mcp-audit.jsonl

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Tool reference

All tools follow a three-tier safety model:

• Read — safe, no side effects, no confirmation needed
• Mutate — defaults to dry_run: true; set dry_run: false to execute
• Destructive — requires confirm: true, or a 2026-07-28 client can complete the server's interactive MRTR confirmation

Kubernetes (k8s__*)

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

ArgoCD (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

Prometheus (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:

• Latency: "Latency increased: 120ms → 480ms (+300%)" or "Latency stable: 125ms"
• Error rate: "Error rate crossed SLO (5%): 7.2%" or "Error rate within SLO: 2.1%"
• Traffic: "Traffic dropped: 500 → 350 req/s (-30%)" or "Traffic spike detected (+150%)"
• Overall assessment: Summary of issues and positive indicators

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.

Loki (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)

# Search logs with custom query
logs__search(query='{service="payments"} |= level="error"', limit=100)

Why this matters:

• Metrics tell what: Prometheus shows you that latency increased or error rate crossed SLO
• Logs tell why: Loki shows you the actual error messages, stack traces, and context around failures
• Complete debugging: Without logs, you can see that something is broken but not understand the root cause

Output format:

• Structured log entries with timestamp, message, service, namespace, and extracted log levels
• Error count summaries and filtering
• Raw LogQL results for detailed analysis

This makes incident investigation complete by combining the "what" (metrics) with the "why" (logs).

PagerDuty (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
pd__summarize_incident	read	🚨 Incident auto-summary - what happened, affected services, probable root cause, current status

pd__summarize_incident

Example usage:

# Get an auto-summary of an incident
pd__summarize_incident(id="ABC123")

What it outputs:

• What happened: Incident title, description, severity, urgency, status, creation time, and duration
• Affected services: Service name, ID, and current status
• Probable root cause: Analysis of trigger alerts and log entries to identify likely causes
• Current status: Current incident state, assignees, acknowledgements, and notes count

Output format:

{
  "what_happened": {
    "title": "API Gateway High Error Rate",
    "description": "5xx error rate exceeded 5% threshold",
    "severity": "high",
    "urgency": "high",
    "status": "acknowledged",
    "createdAt": "2025-01-15T10:30:00Z",
    "updatedAt": "2025-01-15T11:45:00Z",
    "duration": "1h 15m"
  },
  "affected_services": [
    {
      "id": "P123456",
      "name": "API Gateway",
      "status": "critical"
    }
  ],
  "probable_root_cause": "Triggered by: High 5xx error rate from API Gateway pods",
  "current_status": {
    "status": "acknowledged",
    "lastUpdated": "2025-01-15T11:45:00Z",
    "assignees": ["john.doe@company.com"],
    "acknowledgements": 2,
    "notes": 3
  }
}

Why this matters: Instead of manually piecing together incident details from multiple API calls, this tool provides a comprehensive, human-readable summary perfect for:

• Demos: Shows AI's ability to understand and summarize complex incident data
• Real-world use: Quickly understand incident impact without digging through raw data
• Communication: Share concise incident summaries with stakeholders

Helm (helm__*)

Tool	Tier	Description
helm__list_releases	read	List Helm releases with status, chart, app version
helm__get_status	read	Full status of a Helm release
helm__get_values	read	User-supplied or computed values for a release
helm__get_history	read	Revision history of a release
helm__rollback	mutate	Rollback to a previous revision (dry-run by default)

Requirements: Helm CLI binary must be available in PATH.

Example usage:

# List all releases in a namespace
helm__list_releases(namespace="production")

# Check what values a release is using
helm__get_values(name="api-gateway", all_values=true)

# Rollback after a bad deploy
helm__rollback(name="api-gateway", revision=5, dry_run=false)

Cross-Provider Debugging (devops__*)

Tool	Tier	Description
devops__debug_service	read	🔥 Cross-provider incident debugging - aggregates Kubernetes, ArgoCD, Prometheus, and PagerDuty data to diagnose service issues in one command
devops__explain_change	read	🧠 Explain what changed - combines ArgoCD history, Kubernetes rollout history, and Prometheus anomaly window to identify cause of issues
devops__runbook	read	📋 Automated runbook - symptom-based diagnostic that runs targeted checks (crashloop, high-latency, oom, 5xx, pod-pending)
devops__health_report	read	🏥 Cluster health report - one-shot assessment across all providers with overall status (healthy/degraded/critical)
devops__incident_timeline	read	🕐 Incident timeline - unified event timeline across K8s, ArgoCD, Prometheus, and PagerDuty sorted chronologically

devops__debug_service

Example usage:

# Debug a service across all providers
devops__debug_service(service="payments", namespace="default")

What it checks:

• Kubernetes: Pod status, restart counts, readiness, deployment health, recent events
• ArgoCD: Sync status, health status, Git diff detection, deployment history
• Prometheus: Error rate (5xx responses), latency (p95), firing alerts
• PagerDuty: Active incidents matching the service name

Output format:

• Human-readable diagnosis with emoji indicators (⚠️ warnings, ❌ errors)
• Per-provider status sections
• Summary highlighting critical issues
• Raw JSON data for detailed analysis

This is the most powerful tool for incident investigation - it gives you a complete picture of what's wrong with a service in seconds.

devops__explain_change

Example usage:

# Explain what changed in the last hour
devops__explain_change(service="payments", namespace="default", timeframeMinutes=60)

What it analyzes:

• ArgoCD: Deployment history within the timeframe, including revision, author, repo, and chart
• Kubernetes: Current rollout status, replica counts, image tags, and deployment readiness
• Prometheus: Error rate trends, latency patterns, and traffic spikes over the time window

Output format:

• Timeline of recent deployments with full metadata
• Kubernetes rollout status and health
• Metric anomaly detection (error rate spikes, latency issues, traffic changes)
• Correlation analysis that links deployments to metric changes
• Summary with root cause hypothesis

Problem it solves: "Everything was working yesterday… what changed?"

This tool answers that question by correlating deployment events with metric anomalies, helping you quickly identify whether a recent deployment, config change, or external factor caused the issue.

devops__runbook

Example usage:

# Diagnose a crashlooping service
devops__runbook(symptom="crashloop", service="payments", namespace="default")

# Investigate high latency
devops__runbook(symptom="high-latency", service="api-gateway")

Supported symptoms:

Symptom	What it checks
crashloop	Pod status → logs (tail 50) → BackOff events → deployment health
high-latency	p95 latency → resource usage → firing alerts → recent deploys
oom	OOMKilled events → memory usage → pod describe → resource limits
5xx	Error rate → Loki error logs → deployment health
pod-pending	Scheduling events → pending pods → node capacity

Output: Structured JSON with steps_executed[], findings[], and recommended_actions[].

devops__health_report

Example usage:

# Get a full cluster health assessment
devops__health_report(namespace="production")

What it gathers:

• Kubernetes: Unhealthy pods, deployments not at desired replicas
• Prometheus: Count of firing alerts
• ArgoCD: Out-of-sync and unhealthy applications
• PagerDuty: Open incident count

Output: Overall status (healthy / degraded / critical), per-provider sections, and summary. Perfect for morning standup checks or shift handoffs.

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Deployment options

stdio (recommended for local use)

The MCP host launches devops-mcp as a subprocess and communicates over stdin/stdout. Zero network config. Auth comes from the local environment (kubeconfig, env vars). Process lifecycle tied to Claude Desktop.

npx @notharshhaa/devops-mcp
# or with env vars
KUBECONFIG=~/.kube/config npx @notharshhaa/devops-mcp

Stateless Streamable HTTP (shared deployments)

The HTTP entry serves MCP at POST /mcp using the 2026-07-28 stateless protocol. Each request gets a fresh MCP server instance, so requests can land on any replica without session affinity or shared protocol state. The same endpoint also accepts 2025-era Streamable HTTP clients in stateless compatibility mode.

MCP_HTTP_HOST=127.0.0.1 \
PORT=3000 \
MCP_AUTH_TOKEN=your-secret \
npx -y -p @notharshhaa/devops-mcp@latest devops-mcp-http

Connect clients to http://127.0.0.1:3000/mcp. For a container or remote service, set MCP_HTTP_HOST=0.0.0.0 and configure MCP_ALLOWED_HOSTS with the public/proxy hostnames. Put the service behind TLS for team use.

The deprecated devops-mcp-sse binary remains as a temporary alias for the HTTP entry, but /sse, /message, and /ws now return HTTP 410. Legacy HTTP+SSE and non-standard WebSocket clients must migrate to Streamable HTTP.

2026-07-28 behavior

• No initialize requirement or Mcp-Session-Id on modern requests.
• server/discover, per-request client metadata, and MCP-Protocol-Version are handled by the official SDK.
• Mcp-Method and Mcp-Name headers are validated against the JSON-RPC body for gateway routing and authorization.
• server/discover and tools/list advertise deterministic, public cache hints using MCP_CACHE_TTL_MS (default 60 seconds).
• Destructive tools accept confirm: true; modern clients may instead complete an MRTR interactive confirmation. Confirmation state is HMAC-signed, expires after five minutes, and is bound to the exact tool arguments. Global dry-run blocks before prompting.
• MCP_REQUEST_STATE_SECRET must be the same on every replica for MRTR retries to land anywhere. When omitted, the server derives the key from MCP_AUTH_TOKEN, or uses a process-local random key when no token is configured.
• 2025-era Streamable HTTP and stdio clients remain supported. Sessionful HTTP and legacy HTTP+SSE are not.

The built-in MCP_AUTH_TOKEN is a static bearer-token gate, not an OAuth authorization server. For Internet-facing deployments, terminate TLS and enforce your organization’s OAuth/OIDC policy at a gateway or integrate a dedicated identity provider; do not use deprecated Dynamic Client Registration for new deployments.

A minimal docker-compose.yml is available in examples/.

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Security model

devops-mcp is designed for internal use inside a trusted network. That said:

• Kubernetes: Uses standard kubeconfig via @kubernetes/client-node. Supports exec plugins (AWS EKS, GKE). In-cluster: auto-mounts SA token. Add RBAC rules scoped to your desired permissions — run devops-mcp under a dedicated ServiceAccount with minimal verbs. Context selection is fixed by K8S_CONTEXT at startup; the tool only previews changes because runtime switching would affect other callers.
• ArgoCD: Generate a long-lived token: argocd account generate-token --account devops-mcp. Create a dedicated account in argocd-cm with apiKey capability and a role limited to read + sync.
• Prometheus: Usually unauthenticated inside a cluster. If using Grafana Mimir or Thanos with auth, pass a Bearer token. All tools are read-only so minimal permissions are needed.
• PagerDuty: Create a dedicated API key in PagerDuty → API Access → Create New API Key. Use Full Access if you want acknowledge/escalate tools; Read-only if you want a safe-only mode.
• Mutations are dry-run by default. Every mutating tool defaults dry_run: true. The AI must explicitly pass dry_run: false — it won't do this unless the user clearly requests an action.
• Destructive tools require confirmation. Pass confirm: true directly, or use a 2026-07-28 client that supports the server's MRTR confirmation request. DEVOPS_MCP_DRY_RUN=true blocks execution even after confirmation.
• Audit log. Set DEVOPS_MCP_AUDIT_LOG to a file path. Every tool call is written as a JSONL line with timestamp, tool name, parameters, and outcome. Mutations and destructive calls are flagged.
• Global dry-run mode. Set DEVOPS_MCP_DRY_RUN=true to block every executing mutation, even when a caller passes dry_run: false. Safe previews remain available — useful for read-only team deployments.

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