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Kubectl MCP Tool

by rohitg00
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Kubectl MCP Server

Control your entire Kubernetes infrastructure through natural language conversations with AI.

Talk to your clusters like you talk to a DevOps expert. Debug crashed pods, optimize costs, deploy applications, audit security, manage Helm charts, and visualize dashboards, all through natural language in your favorite AI assistant or agents.

GitHub Stars License: MIT Python Kubernetes MCP PyPI npm Docker Tests agentregistry

Installation

Quick Start with npx (Recommended - Zero Install)

# Run directly without installation - works instantly! npx -y kubectl-mcp-server # Or install globally for faster startup npm install -g kubectl-mcp-server

Or install with pip (Python)

# Standard installation pip install kubectl-mcp-server # With interactive UI dashboards (recommended) pip install kubectl-mcp-server[ui]

Related MCP server: MCP Toolkit

📑 Table of Contents

What Can You Do?

Simply ask your AI assistant in natural language:

💬 "Why is my pod crashing?"

  • Instant crash diagnosis with logs, events, and resource analysis

  • Root cause identification with actionable recommendations

💬 "Deploy a Redis cluster with 3 replicas"

  • Creates deployment with best practices

  • Configures services, persistent storage, and health checks

💬 "Show me which pods are wasting resources"

  • AI-powered cost optimization analysis

  • Resource recommendations with potential savings

💬 "Which services can't reach the database?"

  • Network connectivity diagnostics with DNS resolution

  • Service chain tracing from ingress to pods

💬 "Audit security across all namespaces"

  • RBAC permission analysis

  • Secret security scanning and pod security policies

💬 "Show me the cluster dashboard"

  • Interactive HTML dashboards with live metrics

  • Visual timeline of events and resource usage

224 powerful tools | 8 workflow prompts | 8 data resources | Works with all major AI assistants

Why kubectl-mcp-server?

  • 🚀 Stop context-switching - Manage Kubernetes directly from your AI assistant conversations

  • 🧠 AI-powered diagnostics - Get intelligent troubleshooting, not just raw data

  • 💰 Built-in cost optimization - Identify waste and get actionable savings recommendations

  • 🔒 Enterprise-ready - OAuth 2.1 auth, RBAC validation, non-destructive mode, secret masking

  • ⚡ Zero learning curve - Natural language instead of memorizing kubectl commands

  • 🌐 Universal compatibility - Works with Claude, Cursor, Windsurf, Copilot, and 15+ other AI tools

  • 📊 Visual insights - Interactive dashboards and browser automation for web-based tools

  • ☸️ Production-grade - Deploy in-cluster with kMCP, 216 passing tests, active maintenance

From debugging crashed pods to optimizing cluster costs, kubectl-mcp-server is your AI-powered DevOps companion.

Live Demos

Claude Desktop

Claude MCP

Cursor AI

Cursor MCP

Windsurf

Windsurf MCP

Installation

Quick Start with npx (Recommended - Zero Install)

# Run directly without installation - works instantly! npx -y kubectl-mcp-server # Or install globally for faster startup npm install -g kubectl-mcp-server

Or install with pip (Python)

# Standard installation pip install kubectl-mcp-server # With interactive UI dashboards (recommended) pip install kubectl-mcp-server[ui]

Prerequisites

  • Python 3.9+ (for pip installation)

  • Node.js 14+ (for npx installation)

  • kubectl installed and configured

  • Access to a Kubernetes cluster

Docker

# Pull and run with Docker docker pull rohitghumare64/kubectl-mcp-server:latest # Run with stdio transport docker run -i -v $HOME/.kube:/root/.kube:ro rohitghumare64/kubectl-mcp-server:latest # Run with HTTP transport docker run -p 8000:8000 -v $HOME/.kube:/root/.kube:ro rohitghumare64/kubectl-mcp-server:latest --transport sse

Getting Started

1. Test the Server (Optional)

Before integrating with your AI assistant, verify the installation:

# Check if kubectl is configured kubectl cluster-info # Test the MCP server directly kubectl-mcp-server info # List all available tools kubectl-mcp-server tools # Try calling a tool kubectl-mcp-server call get_pods '{"namespace": "kube-system"}'

2. Connect to Your AI Assistant

Choose your favorite AI assistant and add the configuration:

Quick Setup with Your AI Assistant

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

Cursor AI

Add to ~/.cursor/mcp.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

Windsurf

Add to ~/.config/windsurf/mcp.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

Using Python Instead of npx

{ "mcpServers": { "kubernetes": { "command": "python", "args": ["-m", "kubectl_mcp_tool.mcp_server"], "env": { "KUBECONFIG": "/path/to/.kube/config" } } } }

More integrations: GitHub Copilot, Goose, Gemini CLI, Roo Code, and 15+ other clients —> see full configuration guide below.

3. Restart Your AI Assistant

After adding the configuration, restart your AI assistant (GitHub Copilot, Claude Code,Claude Desktop, Cursor, etc.) to load the MCP server.

4. Try These Commands

Start a conversation with your AI assistant and try these:

Troubleshooting:

"Show me all pods in the kube-system namespace" "Why is the nginx-deployment pod crashing?" "Diagnose network connectivity issues in the default namespace"

Deployments:

"Create a deployment for nginx with 3 replicas" "Scale my frontend deployment to 5 replicas" "Roll back the api-server deployment to the previous version"

Cost & Optimization:

"Which pods are using the most resources?" "Show me idle resources that are wasting money" "Analyze cost optimization opportunities in the production namespace"

Security:

"Audit RBAC permissions in all namespaces" "Check for insecure secrets and configurations" "Show me pods running with privileged access"

Helm:

"List all Helm releases in the cluster" "Install Redis from the Bitnami chart repository" "Show me the values for my nginx-ingress Helm release"

Multi-Cluster:

"List all available Kubernetes contexts" "Switch to the production cluster context" "Show me cluster information and version"

MCP Client Compatibility

Works seamlessly with all MCP-compatible AI assistants:

Client

Status

Client

Status

Claude Desktop

✅ Native

Claude Code

✅ Native

Cursor

✅ Native

Windsurf

✅ Native

GitHub Copilot

✅ Native

OpenAI Codex

✅ Native

Gemini CLI

✅ Native

Goose

✅ Native

Roo Code

✅ Native

Kilo Code

✅ Native

Amp

✅ Native

Trae

✅ Native

OpenCode

✅ Native

Kiro CLI

✅ Native

Antigravity

✅ Native

Clawdbot

✅ Native

Droid (Factory)

✅ Native

Any MCP Client

✅ Compatible

All Supported AI Assistants

Claude Code

Add to ~/.config/claude-code/mcp.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

GitHub Copilot (VS Code)

Add to VS Code settings.json:

{ "mcp": { "servers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } } }

Goose

Add to ~/.config/goose/config.yaml:

extensions: kubernetes: command: npx args: - -y - kubectl-mcp-server

Gemini CLI

Add to ~/.gemini/settings.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

Roo Code / Kilo Code

Add to ~/.config/roo-code/mcp.json or ~/.config/kilo-code/mcp.json:

{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["-y", "kubectl-mcp-server"] } } }

Complete Feature Set

224 MCP Tools for Complete Kubernetes Management

Category

Tools

Pods

get_pods, get_logs, get_pod_events, check_pod_health, exec_in_pod, cleanup_pods, get_pod_conditions, get_previous_logs

Deployments

get_deployments, create_deployment, scale_deployment, kubectl_rollout, restart_deployment

Workloads

get_statefulsets, get_daemonsets, get_jobs, get_replicasets

Services & Networking

get_services, get_ingress, get_endpoints, diagnose_network_connectivity, check_dns_resolution, trace_service_chain

Storage

get_persistent_volumes, get_pvcs, get_storage_classes

Config

get_configmaps, get_secrets, get_resource_quotas, get_limit_ranges

Cluster

get_nodes, get_namespaces, get_cluster_info, get_cluster_version, health_check, get_node_metrics, get_pod_metrics

RBAC & Security

get_rbac_roles, get_cluster_roles, get_service_accounts, audit_rbac_permissions, check_secrets_security, get_pod_security_info, get_admission_webhooks

CRDs

get_crds, get_priority_classes

Helm Releases

helm_list, helm_status, helm_history, helm_get_values, helm_get_manifest, helm_get_notes, helm_get_hooks, helm_get_all

Helm Charts

helm_show_chart, helm_show_values, helm_show_readme, helm_show_crds, helm_show_all, helm_search_repo, helm_search_hub

Helm Repos

helm_repo_list, helm_repo_add, helm_repo_remove, helm_repo_update

Helm Operations

install_helm_chart, upgrade_helm_chart, uninstall_helm_chart, helm_rollback, helm_test, helm_template, helm_template_apply

Helm Development

helm_create, helm_lint, helm_package, helm_pull, helm_dependency_list, helm_dependency_update, helm_dependency_build, helm_version, helm_env

Context

get_current_context, switch_context, list_contexts, list_kubeconfig_contexts

Diagnostics

diagnose_pod_crash, detect_pending_pods, get_evicted_pods, compare_namespaces

Operations

kubectl_apply, kubectl_create, kubectl_describe, kubectl_patch, delete_resource, kubectl_cp, backup_resource, label_resource, annotate_resource, taint_node, wait_for_condition

Autoscaling

get_hpa, get_pdb

Cost Optimization

get_resource_recommendations, get_idle_resources, get_resource_quotas_usage, get_cost_analysis, get_overprovisioned_resources, get_resource_trends, get_namespace_cost_allocation, optimize_resource_requests

Advanced

kubectl_generic, kubectl_explain, get_api_resources, port_forward, get_resource_usage, node_management

UI Dashboards

show_pod_logs_ui, show_pods_dashboard_ui, show_resource_yaml_ui, show_cluster_overview_ui, show_events_timeline_ui, render_k8s_dashboard_screenshot

GitOps (Flux/Argo)

gitops_apps_list, gitops_app_get, gitops_app_sync, gitops_app_status, gitops_sources_list, gitops_source_get, gitops_detect_engine

Cert-Manager

certs_list, certs_get, certs_issuers_list, certs_issuer_get, certs_renew, certs_status_explain, certs_challenges_list, certs_requests_list, certs_detect

Policy (Kyverno/Gatekeeper)

policy_list, policy_get, policy_violations_list, policy_explain_denial, policy_audit, policy_detect

Backup (Velero)

backup_list, backup_get, backup_create, backup_delete, restore_list, restore_create, restore_get, backup_locations_list, backup_schedules_list, backup_schedule_create, backup_detect

KEDA Autoscaling

keda_scaledobjects_list, keda_scaledobject_get, keda_scaledjobs_list, keda_triggerauths_list, keda_triggerauth_get, keda_hpa_list, keda_detect

Cilium/Hubble

cilium_policies_list, cilium_policy_get, cilium_endpoints_list, cilium_identities_list, cilium_nodes_list, cilium_status, hubble_flows_query, cilium_detect

Argo Rollouts/Flagger

rollouts_list, rollout_get, rollout_status, rollout_promote, rollout_abort, rollout_retry, rollout_restart, analysis_runs_list, flagger_canaries_list, flagger_canary_get, rollouts_detect

Cluster API

capi_clusters_list, capi_cluster_get, capi_machines_list, capi_machine_get, capi_machinedeployments_list, capi_machinedeployment_scale, capi_machinesets_list, capi_machinehealthchecks_list, capi_clusterclasses_list, capi_cluster_kubeconfig, capi_detect

KubeVirt VMs

kubevirt_vms_list, kubevirt_vm_get, kubevirt_vmis_list, kubevirt_vm_start, kubevirt_vm_stop, kubevirt_vm_restart, kubevirt_vm_pause, kubevirt_vm_unpause, kubevirt_vm_migrate, kubevirt_datasources_list, kubevirt_instancetypes_list, kubevirt_datavolumes_list, kubevirt_detect

Istio/Kiali

istio_virtualservices_list, istio_virtualservice_get, istio_destinationrules_list, istio_gateways_list, istio_peerauthentications_list, istio_authorizationpolicies_list, istio_proxy_status, istio_analyze, istio_sidecar_status, istio_detect

MCP Resources

Access Kubernetes data as browsable resources:

Resource URI

Description

kubeconfig://contexts

List all available kubectl contexts

kubeconfig://current-context

Get current active context

namespace://current

Get current namespace

namespace://list

List all namespaces

cluster://info

Get cluster information

cluster://nodes

Get detailed node information

cluster://version

Get Kubernetes version

cluster://api-resources

List available API resources

manifest://deployments/{ns}/{name}

Get deployment YAML

manifest://services/{ns}/{name}

Get service YAML

manifest://pods/{ns}/{name}

Get pod YAML

manifest://configmaps/{ns}/{name}

Get ConfigMap YAML

manifest://secrets/{ns}/{name}

Get secret YAML (data masked)

manifest://ingresses/{ns}/{name}

Get ingress YAML

MCP Prompts

Pre-built workflow prompts for common Kubernetes operations:

Prompt

Description

troubleshoot_workload

Comprehensive troubleshooting guide for pods/deployments

deploy_application

Step-by-step deployment workflow

security_audit

Security scanning and RBAC analysis workflow

cost_optimization

Resource optimization and cost analysis workflow

disaster_recovery

Backup and recovery planning workflow

debug_networking

Network debugging for services and connectivity

scale_application

Scaling guide with HPA/VPA best practices

upgrade_cluster

Kubernetes cluster upgrade planning

Key Capabilities

  • 🤖 224 Powerful Tools - Complete Kubernetes management from pods to security

  • 🎯 8 AI Workflow Prompts - Pre-built workflows for common operations

  • 📊 8 MCP Resources - Browsable Kubernetes data exposure

  • 🎨 6 Interactive Dashboards - HTML UI tools for visual cluster management

  • 🌐 26 Browser Tools - Web automation with cloud provider support

  • 🔄 93 Ecosystem Tools - GitOps, Cert-Manager, Policy, Backup, KEDA, Cilium, Rollouts, CAPI, KubeVirt, Istio

  • ⚡ Multi-Transport - stdio, SSE, HTTP, streamable-http

  • 🔐 Security First - Non-destructive mode, secret masking, RBAC validation

  • 🏥 Advanced Diagnostics - AI-powered troubleshooting and cost optimization

  • ☸️ Multi-Cluster - Target any cluster via context parameter in every tool

  • 🎡 Full Helm v3 - Complete chart lifecycle management

  • 🔧 Powerful CLI - Shell-friendly tool discovery and direct calling

  • 🐳 Cloud Native - Deploy in-cluster with kMCP or kagent

Using the CLI

The built-in CLI lets you explore and test tools without an AI assistant:

# List all tools with descriptions kubectl-mcp-server tools -d # Search for pod-related tools kubectl-mcp-server grep "*pod*" # Show specific tool schema kubectl-mcp-server tools get_pods # Call a tool directly kubectl-mcp-server call get_pods '{"namespace": "kube-system"}' # Pipe JSON from stdin echo '{"namespace": "default"}' | kubectl-mcp-server call get_pods # Check dependencies kubectl-mcp-server doctor # Show/switch Kubernetes context kubectl-mcp-server context kubectl-mcp-server context minikube # List resources and prompts kubectl-mcp-server resources kubectl-mcp-server prompts # Show server info kubectl-mcp-server info

CLI Features

  • Structured errors: Actionable error messages with suggestions

  • Colorized output: Human-readable with JSON mode for scripting (--json)

  • NO_COLOR support: Respects NO_COLOR environment variable

  • Stdin support: Pipe JSON arguments to commands

Advanced Configuration

Transport Modes

The server supports multiple transport protocols:

# stdio (default) - Best for Claude Desktop, Cursor, Windsurf kubectl-mcp-server # or: python -m kubectl_mcp_tool.mcp_server # SSE - Server-Sent Events for web clients kubectl-mcp-server --transport sse --port 8000 # HTTP - Standard HTTP for REST clients kubectl-mcp-server --transport http --port 8000 # streamable-http - For agentgateway integration kubectl-mcp-server --transport streamable-http --port 8000

Transport Options:

  • --transport: Choose from stdio, sse, http, streamable-http (default: stdio)

  • --host: Bind address (default: 0.0.0.0)

  • --port: Port for network transports (default: 8000)

  • --non-destructive: Enable read-only mode (blocks delete, apply, create operations)

Environment Variables

Core Settings:

Variable

Description

Default

KUBECONFIG

Path to kubeconfig file

~/.kube/config

MCP_DEBUG

Enable verbose logging

false

MCP_LOG_FILE

Log file path

None (stdout)

Authentication (Enterprise):

Variable

Description

Default

MCP_AUTH_ENABLED

Enable OAuth 2.1 authentication

false

MCP_AUTH_ISSUER

OAuth 2.0 Authorization Server URL

-

MCP_AUTH_JWKS_URI

JWKS endpoint URL

Auto-derived

MCP_AUTH_AUDIENCE

Expected token audience

kubectl-mcp-server

MCP_AUTH_REQUIRED_SCOPES

Required OAuth scopes

mcp:tools

Browser Automation (Optional):

Variable

Description

Default

MCP_BROWSER_ENABLED

Enable browser automation tools

false

MCP_BROWSER_PROVIDER

Cloud provider (browserbase/browseruse)

None

MCP_BROWSER_PROFILE

Persistent profile path

None

MCP_BROWSER_CDP_URL

Remote CDP WebSocket URL

None

MCP_BROWSER_PROXY

Proxy server URL

None

Optional: Interactive Dashboards (6 UI Tools)

Get beautiful HTML dashboards for visual cluster management.

Installation:

# Install with UI support pip install kubectl-mcp-server[ui]

6 Dashboard Tools:

  • 📊 show_pods_dashboard_ui - Real-time pod status table

  • 📝 show_pod_logs_ui - Interactive log viewer with search

  • 🎯 show_cluster_overview_ui - Complete cluster dashboard

  • ⚡ show_events_timeline_ui - Events timeline with filtering

  • 📄 show_resource_yaml_ui - YAML viewer with syntax highlighting

  • 📸 render_k8s_dashboard_screenshot - Export dashboards as PNG

Features:

  • 🎨 Dark theme optimized for terminals (Catppuccin)

  • 🔄 Graceful fallback to JSON for incompatible clients

  • 🖼️ Screenshot rendering for universal compatibility

  • 🚀 Zero external dependencies

Works With: Goose, LibreChat, Nanobot (full HTML UI) | Claude Desktop, Cursor, others (JSON + screenshots)

Optional: Browser Automation (26 Tools)

Automate web-based Kubernetes operations with agent-browser integration.

Quick Setup:

# Install agent-browser npm install -g agent-browser agent-browser install # Enable browser tools export MCP_BROWSER_ENABLED=true kubectl-mcp-server

What You Can Do:

  • 🌐 Test deployed apps via Ingress URLs

  • 📸 Screenshot Grafana, ArgoCD, or any K8s dashboard

  • ☁️ Automate cloud console operations (EKS, GKE, AKS)

  • 🏥 Health check web applications

  • 📄 Export monitoring dashboards as PDF

  • 🔐 Test authentication flows with persistent sessions

26 Available Tools: browser_open, browser_screenshot, browser_click, browser_fill, browser_test_ingress, browser_screenshot_grafana, browser_health_check, and 19 more

Advanced Features:

  • Cloud providers: Browserbase, Browser Use

  • Persistent browser profiles

  • Remote CDP connections

  • Session management

Enterprise: OAuth 2.1 Authentication

Secure your MCP server with OAuth 2.1 authentication (RFC 9728).

export MCP_AUTH_ENABLED=true export MCP_AUTH_ISSUER=https://your-idp.example.com export MCP_AUTH_AUDIENCE=kubectl-mcp-server kubectl-mcp-server --transport http --port 8000

Supported Identity Providers: Okta, Auth0, Keycloak, Microsoft Entra ID, Google OAuth, and any OIDC-compliant provider.

Use Case: Multi-tenant environments, compliance requirements, audit logging.

Integrations & Ecosystem

Docker MCP Toolkit

Works with Docker MCP Toolkit:

docker mcp server add kubectl-mcp-server mcp/kubectl-mcp-server:latest docker mcp server configure kubectl-mcp-server --volume "$HOME/.kube:/root/.kube:ro" docker mcp server enable kubectl-mcp-server docker mcp client connect claude

agentregistry

Install from the centralized agentregistry:

# Install arctl CLI curl -fsSL https://raw.githubusercontent.com/agentregistry-dev/agentregistry/main/scripts/install.sh | bash # Install kubectl-mcp-server arctl mcp install io.github.rohitg00/kubectl-mcp-server

Available via: PyPI (uvx), npm (npx), OCI (docker.io/rohitghumare64/kubectl-mcp-server)

agentgateway

Route to multiple MCP servers through agentgateway:

# Start with streamable-http kubectl-mcp-server --transport streamable-http --port 8000 # Configure gateway cat > gateway.yaml <<EOF binds: - port: 3000 listeners: - routes: - backends: - mcp: targets: - name: kubectl-mcp-server mcp: host: http://localhost:8000/mcp EOF # Start gateway agentgateway --config gateway.yaml

Connect clients to http://localhost:3000/mcp for unified access to all 224 tools.

In-Cluster Deployment

Option 1: kMCP (Recommended)

Deploy with kMCP - a control plane for MCP servers:

# Install kMCP curl -fsSL https://raw.githubusercontent.com/kagent-dev/kmcp/refs/heads/main/scripts/get-kmcp.sh | bash kmcp install # Deploy kubectl-mcp-server (easiest) kmcp deploy package --deployment-name kubectl-mcp-server \ --manager npx --args kubectl-mcp-server # Or with Docker image kmcp deploy --file deploy/kmcp/kmcp.yaml --image rohitghumare64/kubectl-mcp-server:latest

See kMCP quickstart for details.

Option 2: Standard Kubernetes

Deploy with kubectl/kustomize:

# Using kustomize (recommended) kubectl apply -k deploy/kubernetes/ # Or individual manifests kubectl apply -f deploy/kubernetes/namespace.yaml kubectl apply -f deploy/kubernetes/rbac.yaml kubectl apply -f deploy/kubernetes/deployment.yaml kubectl apply -f deploy/kubernetes/service.yaml # Access via port-forward kubectl port-forward -n kubectl-mcp svc/kubectl-mcp-server 8000:8000

See deploy/ directory for all manifests and configuration options.

Option 3: kagent (AI Agent Framework)

Integrate with kagent - a CNCF Kubernetes-native AI agent framework:

# Install kagent brew install kagent kagent install --profile demo # Register as ToolServer kubectl apply -f deploy/kagent/toolserver-stdio.yaml # Open dashboard kagent dashboard

Your AI agents now have access to all 224 Kubernetes tools. See kagent quickstart.

Architecture

┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐ │ AI Assistant │────▶│ MCP Server │────▶│ Kubernetes API │ │ (Claude/Cursor) │◀────│ (kubectl-mcp) │◀────│ (kubectl) │ └─────────────────┘ └──────────────────┘ └─────────────────┘

The MCP server implements the Model Context Protocol, translating natural language requests into kubectl operations.

Modular Structure

kubectl_mcp_tool/ ├── mcp_server.py # Main server (FastMCP, transports) ├── tools/ # 224 MCP tools organized by category │ ├── pods.py # Pod management & diagnostics │ ├── deployments.py # Deployments, StatefulSets, DaemonSets │ ├── core.py # Namespaces, ConfigMaps, Secrets │ ├── cluster.py # Context/cluster management │ ├── networking.py # Services, Ingress, NetworkPolicies │ ├── storage.py # PVCs, StorageClasses, PVs │ ├── security.py # RBAC, ServiceAccounts, PodSecurity │ ├── helm.py # Complete Helm v3 operations │ ├── operations.py # kubectl apply/patch/describe/etc │ ├── diagnostics.py # Metrics, namespace comparison │ ├── cost.py # Resource optimization & cost analysis │ ├── ui.py # MCP-UI interactive dashboards │ ├── gitops.py # GitOps (Flux/ArgoCD) │ ├── certs.py # Cert-Manager │ ├── policy.py # Policy (Kyverno/Gatekeeper) │ ├── backup.py # Backup (Velero) │ ├── keda.py # KEDA autoscaling │ ├── cilium.py # Cilium/Hubble network observability │ ├── rollouts.py # Argo Rollouts/Flagger │ ├── capi.py # Cluster API │ ├── kubevirt.py # KubeVirt VMs │ └── kiali.py # Istio/Kiali service mesh ├── resources/ # 8 MCP Resources for data exposure ├── prompts/ # 8 MCP Prompts for workflows └── cli/ # CLI interface

Agent Skills (24 Skills for AI Coding Agents)

Extend your AI coding agent with Kubernetes expertise using our Agent Skills library. Skills provide specialized knowledge and workflows that agents can load on demand.

Quick Install

# Copy all skills to Claude cp -r kubernetes-skills/claude/* ~/.claude/skills/ # Or install specific skills cp -r kubernetes-skills/claude/k8s-helm ~/.claude/skills/

Available Skills (24)

Category

Skills

Core Resources

k8s-core, k8s-networking, k8s-storage

Workloads

k8s-deploy, k8s-operations, k8s-helm

Observability

k8s-diagnostics, k8s-troubleshoot, k8s-incident

Security

k8s-security, k8s-policy, k8s-certs

GitOps

k8s-gitops, k8s-rollouts

Scaling

k8s-autoscaling, k8s-cost, k8s-backup

Multi-Cluster

k8s-multicluster, k8s-capi, k8s-kubevirt

Networking

k8s-service-mesh, k8s-cilium

Tools

k8s-browser, k8s-cli

Convert to Other Agents

Use SkillKit to convert skills to your preferred AI agent format:

npm install -g skillkit # Convert to Cursor format skillkit translate kubernetes-skills/claude --to cursor --output .cursor/rules/ # Convert to Codex format skillkit translate kubernetes-skills/claude --to codex --output ./

Supported agents: Claude, Cursor, Codex, Gemini CLI, GitHub Copilot, Goose, Windsurf, Roo, Amp, and more.

See kubernetes-skills/README.md for full documentation.

Multi-Cluster Support

Seamlessly manage multiple Kubernetes clusters through natural language. Every tool supports an optional context parameter to target any cluster without switching contexts.

Context Parameter (v1.15.0)

All 224 tools accept an optional context parameter to target specific clusters:

Talk to your AI assistant:

"List pods in the production cluster" "Get deployments from staging context" "Show logs from the api-pod in the dev cluster" "Compare namespaces between production and staging clusters"

Direct tool calls with context:

# Target a specific cluster context kubectl-mcp-server call get_pods '{"namespace": "default", "context": "production"}' # Get deployments from staging kubectl-mcp-server call get_deployments '{"namespace": "app", "context": "staging"}' # Install Helm chart to production cluster kubectl-mcp-server call install_helm_chart '{"name": "redis", "chart": "bitnami/redis", "namespace": "cache", "context": "production"}' # Compare resources across clusters kubectl-mcp-server call compare_namespaces '{"namespace1": "prod-ns", "namespace2": "staging-ns", "context": "production"}'

Context Management

Talk to your AI assistant:

"List all available Kubernetes contexts" "Switch to the production cluster" "Show me details about the staging context" "What's the current cluster I'm connected to?"

Or use the CLI directly:

kubectl-mcp-server context # Show current context kubectl-mcp-server context production # Switch context kubectl-mcp-server call list_contexts_tool # List all contexts via MCP

How It Works

  • If context is omitted, the tool uses your current kubectl context

  • If context is specified, the tool targets that cluster directly

  • Response includes "context": "production" or "context": "current" for clarity

  • Works with all kubeconfig setups and respects KUBECONFIG environment variable

  • No need to switch contexts for cross-cluster operations

Development & Testing

Setup Development Environment

# Clone the repository git clone https://github.com/rohitg00/kubectl-mcp-server.git cd kubectl-mcp-server # Create virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install development dependencies pip install -r requirements-dev.txt

Running Tests

# Run all tests pytest tests/ -v # Run specific test file pytest tests/test_tools.py -v # Run with coverage pytest tests/ --cov=kubectl_mcp_tool --cov-report=html # Run only unit tests pytest tests/ -v -m unit

Test Structure

tests/ ├── __init__.py # Test package ├── conftest.py # Shared fixtures and mocks ├── test_tools.py # Unit tests for 224 MCP tools ├── test_resources.py # Tests for 8 MCP Resources ├── test_prompts.py # Tests for 8 MCP Prompts └── test_server.py # Server initialization tests

234 tests covering: tool registration, resource exposure, prompt generation, server initialization, non-destructive mode, secret masking, error handling, transport methods, CLI commands, browser automation, and ecosystem tools.

Code Quality

# Format code black kubectl_mcp_tool tests # Sort imports isort kubectl_mcp_tool tests # Lint flake8 kubectl_mcp_tool tests # Type checking mypy kubectl_mcp_tool

Contributing

We ❤️ contributions! Whether it's bug reports, feature requests, documentation improvements, or code contributions.

Ways to contribute:

  • 🐛 Report bugs via GitHub Issues

  • 💡 Suggest features or improvements

  • 📝 Improve documentation

  • 🔧 Submit pull requests

  • ⭐ Star the project if you find it useful!

Development setup: See Development & Testing section above.

Before submitting a PR:

  1. Run tests: pytest tests/ -v

  2. Format code: black kubectl_mcp_tool tests

  3. Check linting: flake8 kubectl_mcp_tool tests

Support & Community

License

MIT License - see LICENSE for details.

Links & Resources

Package Repositories:

Project:

Ecosystem:

Made with ❤️ for the Kubernetes and AI community

If kubectl-mcp-server makes your DevOps life easier, give it a ⭐ on GitHub!

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