Unified MCP server for Kubernetes, ArgoCD, Prometheus, and PagerDuty
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Devops MCP.
k8s__list_podsList pods with status, restarts, node, age
k8s__get_pod_logsTail or stream logs from a pod container
k8s__describe_resourceFull describe for any resource type
k8s__get_eventsCluster or namespace events, filterable by reason
k8s__list_deploymentsDeployments with replica counts and rollout health
k8s__get_resource_usageCPU/mem usage per pod via metrics-server
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):
Restart Claude Desktop. The devops server will appear in the tools list.
Requires Node.js 20 or newer.
All config is via environment variables. Only set the ones for providers you actually use — providers with missing config are silently skipped.
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 |
k8s__get_events | read | Cluster or namespace events, filterable by reason |
k8s__list_deployments | read | Deployments with replica counts and rollout health |
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 — 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:
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 |
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