kubectl-mcp-server
Advanced tools
A Model Context Protocol (MCP) server for Kubernetes with 270+ tools, 8 resources, and 8 prompts for AI assistants
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.
# Run directly without installation - works instantly!
npx -y kubectl-mcp-server
# Or install globally for faster startup
npm install -g kubectl-mcp-server
# Standard installation
pip install kubectl-mcp-server
# With interactive UI dashboards (recommended)
pip install kubectl-mcp-server[ui]
Simply ask your AI assistant in natural language:
💬 "Why is my pod crashing?"
💬 "Deploy a Redis cluster with 3 replicas"
💬 "Show me which pods are wasting resources"
💬 "Which services can't reach the database?"
💬 "Audit security across all namespaces"
💬 "Show me the cluster dashboard"
253 powerful tools | 8 workflow prompts | 8 data resources | Works with all major AI assistants
From debugging crashed pods to optimizing cluster costs, kubectl-mcp-server is your AI-powered DevOps companion.
# Run directly without installation - works instantly!
npx -y kubectl-mcp-server
# Or install globally for faster startup
npm install -g kubectl-mcp-server
# Standard installation
pip install kubectl-mcp-server
# With interactive UI dashboards (recommended)
pip install kubectl-mcp-server[ui]
# Install specific version directly from GitHub release (replace {VERSION} with desired version)
pip install https://github.com/rohitg00/kubectl-mcp-server/releases/download/v{VERSION}/kubectl_mcp_server-{VERSION}-py3-none-any.whl
# Example: Install v1.19.0
pip install https://github.com/rohitg00/kubectl-mcp-server/releases/download/v1.19.0/kubectl_mcp_server-1.19.0-py3-none-any.whl
# Or install latest from git
pip install git+https://github.com/rohitg00/kubectl-mcp-server.git
# Pull from Docker Hub
docker pull rohitghumare64/kubectl-mcp-server:latest
# Or pull from GitHub Container Registry
docker pull ghcr.io/rohitg00/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
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"}'
Choose your favorite AI assistant and add the configuration:
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
Add to ~/.config/windsurf/mcp.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
{
"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.
After adding the configuration, restart your AI assistant (GitHub Copilot, Claude Code,Claude Desktop, Cursor, etc.) to load the MCP server.
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"
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 |
Add to ~/.config/claude-code/mcp.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
Add to VS Code settings.json:
{
"mcp": {
"servers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
}
Add to ~/.config/goose/config.yaml:
extensions:
kubernetes:
command: npx
args:
- -y
- kubectl-mcp-server
Add to ~/.gemini/settings.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
Add to ~/.config/roo-code/mcp.json or ~/.config/kilo-code/mcp.json:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}
| 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 |
| vCluster (vind) | vind_detect_tool, vind_list_clusters_tool, vind_status_tool, vind_get_kubeconfig_tool, vind_logs_tool, vind_create_cluster_tool, vind_delete_cluster_tool, vind_pause_tool, vind_resume_tool, vind_connect_tool, vind_disconnect_tool, vind_upgrade_tool, vind_describe_tool, vind_platform_start_tool |
| kind (K8s in Docker) | kind_detect_tool, kind_version_tool, kind_list_clusters_tool, kind_get_nodes_tool, kind_get_kubeconfig_tool, kind_export_logs_tool, kind_cluster_info_tool, kind_node_labels_tool, kind_create_cluster_tool, kind_delete_cluster_tool, kind_delete_all_clusters_tool, kind_load_image_tool, kind_load_image_archive_tool, kind_build_node_image_tool, kind_set_kubeconfig_tool |
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 |
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 |
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
--json)NO_COLOR environment variableThe 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)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 |
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 tableshow_pod_logs_ui - Interactive log viewer with searchshow_cluster_overview_ui - Complete cluster dashboardshow_events_timeline_ui - Events timeline with filteringshow_resource_yaml_ui - YAML viewer with syntax highlightingrender_k8s_dashboard_screenshot - Export dashboards as PNGFeatures:
Works With: Goose, LibreChat, Nanobot (full HTML UI) | Claude Desktop, Cursor, others (JSON + screenshots)
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:
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:
A standalone npm package that provides beautiful, interactive UI dashboards for Kubernetes management using the MCP ext-apps SDK.
Installation:
# Via npm
npm install -g kubectl-mcp-app
# Or via npx (no install)
npx kubectl-mcp-app
Claude Desktop Configuration:
{
"mcpServers": {
"kubectl-app": {
"command": "npx",
"args": ["kubectl-mcp-app"]
}
}
}
8 Interactive UI Tools:
| Tool | Description |
|---|---|
k8s-pods | Interactive pod viewer with filtering, sorting, status indicators |
k8s-logs | Real-time log viewer with syntax highlighting and search |
k8s-deploy | Deployment dashboard with rollout status, scaling, rollback |
k8s-helm | Helm release manager with upgrade/rollback actions |
k8s-cluster | Cluster overview with node health and resource metrics |
k8s-cost | Cost analyzer with waste detection and recommendations |
k8s-events | Events timeline with type filtering and grouping |
k8s-network | Network topology graph showing Services/Pods/Ingress |
Features:
More Info: See kubectl-mcp-app/README.md for full documentation.
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.
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
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)
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 253 tools.
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.
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.
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 253 Kubernetes tools. See kagent quickstart.
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ 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.
kubectl_mcp_tool/
├── mcp_server.py # Main server (FastMCP, transports)
├── tools/ # 253 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
│ └── vind.py # vCluster (virtual clusters)
├── resources/ # 8 MCP Resources for data exposure
├── prompts/ # 8 MCP Prompts for workflows
└── cli/ # CLI interface
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.
# 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/
| 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, k8s-vind |
| Networking | k8s-service-mesh, k8s-cilium |
| Tools | k8s-browser, k8s-cli |
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.
Seamlessly manage multiple Kubernetes clusters through natural language. Every tool supports an optional context parameter to target any cluster without switching contexts.
Most kubectl-backed tools accept an optional context parameter to target specific clusters.
Note: vCluster (vind) and kind tools run via their local CLIs and do not accept the context parameter.
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"}'
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
context is omitted, the tool uses your current kubectl contextcontext is specified, the tool targets that cluster directly"context": "production" or "context": "current" for clarityKUBECONFIG environment variable# 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
# 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
tests/
├── __init__.py # Test package
├── conftest.py # Shared fixtures and mocks
├── test_tools.py # Unit tests for 253 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.
# 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
We ❤️ contributions! Whether it's bug reports, feature requests, documentation improvements, or code contributions.
Ways to contribute:
Development setup: See Development & Testing section above.
Before submitting a PR:
pytest tests/ -vblack kubectl_mcp_tool testsflake8 kubectl_mcp_tool testsMIT License - see LICENSE for details.
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!
FAQs
A Model Context Protocol (MCP) server for Kubernetes with 270+ tools, 8 resources, and 8 prompts for AI assistants
The npm package kubectl-mcp-server receives a total of 278 weekly downloads. As such, kubectl-mcp-server popularity was classified as not popular.
We found that kubectl-mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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