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
devops__*	Cross-provider incident debugging	Aggregates all providers

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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", "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"
      }
    }
  }
}

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=...

Local dev / test

npx devops-mcp
# or clone and run:
git clone https://github.com/your-handle/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

# ── Transport ────────────────────────────────────────────────
# For stdio mode (default): no transport config needed
# For SSE mode: set these env vars
PORT=3000                                # SSE mode only
MCP_AUTH_TOKEN=shared-secret            # Bearer token for SSE authentication

# ── 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 as an explicit parameter

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
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__list_contexts	read	All kubeconfig contexts and the active one
k8s__switch_context	mutate	Switch active context (session-scoped)
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 confirm: true

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	Roll back to a specific history revision
argo__terminate_op	mutate	Cancel an in-progress sync operation

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__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.

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	Acknowledge — suppresses further notifications
pd__add_note	mutate	Append a note to an incident timeline
pd__escalate_incident	destructive	Escalate to a different policy — requires confirm: true

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 the cause of issues

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.

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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

SSE / HTTP (for shared teams)

Server runs as a persistent HTTP service. Claude connects over Server-Sent Events. Enables multiple users sharing one server. Needs TLS + a bearer token or mTLS in front. Deploy via Docker on an internal bastion.

npx @notharshhaa/devops-mcp-sse
# or with env vars
PORT=3000 MCP_AUTH_TOKEN=your-secret npx @notharshhaa/devops-mcp-sse

For team use, put it behind a TLS-terminating reverse proxy (Caddy, nginx, Traefik). A minimal docker-compose.yml is in the examples/ directory.

WebSocket (optional extra)

Run @notharshhaa/devops-mcp with WebSocket transport for real-time bidirectional communication (not in reference implementation).

TRANSPORT=websocket PORT=3000 MCP_AUTH_TOKEN=your-secret npx @notharshhaa/devops-mcp

Connect to ws://localhost:3000/ws with the auth token in the Authorization header.

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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.
• 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 confirm: true. This parameter is never passed by default; it requires the user to explicitly approve.
• 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 prevent all mutations — useful for read-only team deployments.

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Architecture

Client / UI agents (Claude Desktop, Claude Code, etc.)
       │
       ▼
  Transport Layer
  ┌──────────────────────────────┐
  │ stdio | SSE | WebSocket      │  ← Multiple transport support
  │ Authentication (token/JWT)    │  ← Dynamic auth system
  └──────────────────────────────┘
       │
       ▼
  Server & Auth/Registry
  ┌──────────────────────────────┐
  │ Tool registry & routing      │
  │ Dynamic auth manager         │  ← Session-based auth
  │ Request multiplexing         │  ← Concurrent request handling
  │ Audit logging                │
  └──────────────────────────────┘
       │
       ▼
  ┌────┬────┬────┐
  k8s  argo prom  pd  ← Provider modules
  │    │    │     │
  K8s  Argo Prom  PD  ← API clients
  API  API  HTTP  API
       │
       ▼
  Cross-cutting Concerns
  ┌──────────────────────────────┐
  │ Dry-run guard                │
  │ Audit logger                 │
  │ Error normalization          │
  │ Config loader                │
  └──────────────────────────────┘

Key architectural features:

• Multi-transport support: stdio and SSE transports using official MCP SDK
• Simple authentication: Bearer token for SSE transport (matches reference pattern)
• Provider isolation: Each provider (k8s, argo, prom, pd) is a self-contained module
• Cross-cutting concerns: Dry-run enforcement, audit logging, and error normalization applied consistently across all tools

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Contributing

Contributions are welcome. The most useful areas:

• New providers — Grafana, Datadog, Vault, Terraform Cloud, Flux CD
• New tools — within existing providers (e.g. k8s__get_node_pressure, argo__get_app_logs)
• Better output formatting — richer structured responses for specific resource types
• Tests — unit tests for provider logic using mocked clients

Adding a new provider

1. Create src/providers/yourprovider/ with index.ts, client.ts, and one file per resource group.
2. Register it in src/server.ts.
3. Add config keys to .env.example and src/config.ts.
4. Document tools in this README following the existing table format.
5. Open a PR.

Local development

git clone https://github.com/your-handle/devops-mcp
cd devops-mcp
npm install
cp .env.example .env
npm run dev        # tsx watch — restarts on file change

Run against a local kind/minikube cluster for Kubernetes testing. Use DEVOPS_MCP_DRY_RUN=true to prevent accidental mutations during development.

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Roadmap

• Grafana provider (grafana__*) — dashboards, annotations, datasources
• Flux CD provider (flux__*) — kustomizations, helm releases, image automation
• Terraform Cloud provider (tfc__*) — workspace runs, state, variables
• HashiCorp Vault provider (vault__*) — secret read (never write), lease status
• Datadog provider (dd__*) — metrics, monitors, events
• Web UI for SSE mode — connection status, live audit log, provider health

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License

MIT — see LICENSE.

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Built for DevOps and platform engineers who want AI that actually knows what's happening in their cluster.