# mcp-kubernetes **Repository Path**: mirrors_Azure/mcp-kubernetes ## Basic Information - **Project Name**: mcp-kubernetes - **Description**: A Model Context Protocol (MCP) server that enables AI assistants to interact with Kubernetes clusters. It serves as a bridge between AI tools (like Claude, Cursor, and GitHub Copilot) and Kubernetes - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-05-28 - **Last Updated**: 2026-03-28 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # mcp-kubernetes The mcp-kubernetes is a Model Context Protocol (MCP) server that enables AI assistants to interact with Kubernetes clusters. It serves as a bridge between AI tools (like Claude, Cursor, and GitHub Copilot) and Kubernetes, translating natural language requests into Kubernetes operations and returning the results in a format the AI tools can understand. It allows AI tools to: - Query Kubernetes resources - Execute kubectl commands - Manage Kubernetes clusters through natural language interactions - Diagnose and interpret the states of Kubernetes resources ## How it works ![](assets/mcp-kubernetes-server.png) ## How to install ### Docker Get your kubeconfig file for your Kubernetes cluster and setup in the mcpServers (replace src path with your kubeconfig path): ```json { "mcpServers": { "kubernetes": { "command": "docker", "args": [ "run", "-i", "--rm", "--mount", "type=bind,src=/home/username/.kube/config,dst=/home/mcp/.kube/config", "ghcr.io/azure/mcp-kubernetes" ] } } } ``` ### Local
Install kubectl Install [kubectl](https://kubernetes.io/docs/tasks/tools/) if it's not installed yet and add it to your PATH, e.g. ```bash # For Linux curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl" # For MacOS curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/darwin/arm64/kubectl" ```
Install helm Install [helm](https://helm.sh/docs/intro/install/) if it's not installed yet and add it to your PATH, e.g. ```bash curl -sSL https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash ```

Config your MCP servers in [Claude Desktop](https://claude.ai/download), [Cursor](https://www.cursor.com/), [ChatGPT Copilot](https://marketplace.visualstudio.com/items?itemName=feiskyer.chatgpt-copilot), [Github Copilot](https://github.com/features/copilot) and other supported AI clients, e.g. ```json { "mcpServers": { "kubernetes": { "command": "", "args": ["--transport", "stdio"], "env": { "KUBECONFIG": "" } } } } ``` ### Options Environment variables: - `KUBECONFIG`: Path to your kubeconfig file, e.g. `/home//.kube/config`. - `USE_LEGACY_TOOLS`: Set to `true` to use multiple specialized kubectl tools instead of the unified `call_kubectl` tool (default: `false`). Command line arguments: ```sh Usage of ./mcp-kubernetes: --access-level string Access level (readonly, readwrite, or admin) (default "readonly") --additional-tools string Comma-separated list of additional tools to support (kubectl is always enabled). Available: helm,cilium,hubble --allow-namespaces string Comma-separated list of namespaces to allow (empty means all allowed) --host string Host to listen for the server (only used with transport sse or streamable-http) (default "127.0.0.1") --otlp-endpoint string OTLP endpoint for OpenTelemetry traces (e.g. localhost:4317, default "") --port int Port to listen for the server (only used with transport sse or streamable-http) (default 8000) --timeout int Timeout for command execution in seconds, default is 60s (default 60) --transport string Transport mechanism to use (stdio, sse or streamable-http) (default "stdio") ``` ### Unified vs Legacy Tools By default, mcp-kubernetes uses a single unified `call_kubectl` tool that consolidates all kubectl operations into one tool interface. This significantly reduces context consumption while maintaining full functionality. To use the legacy mode with multiple specialized tools (6-7 separate tools), set the environment variable: ```json { "mcpServers": { "kubernetes": { "command": "mcp-kubernetes", "env": { "USE_LEGACY_TOOLS": "true" } } } } ``` ### Access Levels The `--access-level` flag controls what operations are allowed: - **`readonly`** (default): Only read operations are allowed (get, describe, logs, etc.) - **`readwrite`**: Read and write operations are allowed (create, delete, apply, etc.) - **`admin`**: All operations are allowed, including admin operations (cordon, drain, taint, etc.) Tools and operations are filtered at registration time based on the access level, so AI assistants only see operations they can actually use. Example configurations: ```json // Read-only access (default) { "mcpServers": { "kubernetes": { "command": "mcp-kubernetes" } } } // Read-write access { "mcpServers": { "kubernetes": { "command": "mcp-kubernetes", "args": ["--access-level", "readwrite"] } } } // Admin access { "mcpServers": { "kubernetes": { "command": "mcp-kubernetes", "args": ["--access-level", "admin"] } } } ``` ## Usage Ask any questions about Kubernetes cluster in your AI client. The MCP tools make it easier for AI assistants to understand and use kubectl operations. ### Example Queries ```txt What is the status of my Kubernetes cluster? What is wrong with my nginx pod? Show me all deployments in the production namespace Scale my web deployment to 5 replicas Check if I have permission to create pods What is my current kubectl context? List all available kubectl contexts Switch to the production context ``` ## Available Tools ### Unified Tool (Default) By default, mcp-kubernetes uses a single unified `call_kubectl` tool that handles all kubectl operations. This approach significantly reduces context consumption compared to the legacy multi-tool approach. **call_kubectl** - Execute kubectl commands - **Available in**: All access levels (operations filtered by access level) - **Parameters**: - `command`: The full kubectl command to execute including 'kubectl' prefix (e.g., "kubectl get pods -n default", "kubectl apply -f deployment.yaml") - **Examples**: ```bash # Get pods command: "kubectl get pods -n default" # Apply configuration command: "kubectl apply -f deployment.yaml" # Scale deployment command: "kubectl scale deployment nginx --replicas=3" ``` ### Legacy Tools (Optional) When `USE_LEGACY_TOOLS=true`, the mcp-kubernetes server provides multiple specialized kubectl tools that group related operations together. Tools are automatically filtered based on your access level. #### Kubectl Tools
kubectl_resources - Manage Kubernetes resources **Available in**: readonly, readwrite, admin Handles CRUD operations on Kubernetes resources and node management. In readonly mode, only supports `get` and `describe` operations. Node operations (cordon, uncordon, drain, taint) are available in admin mode only. **Parameters:** - `operation`: The operation to perform (get, describe, create, delete, apply, patch, replace, cordon, uncordon, drain, taint) - `resource`: The resource type (e.g., pods, deployments, services, nodes) or empty for file-based operations - `args`: Additional arguments like resource names, namespaces, and flags **Examples:** ```bash # Get all pods operation: "get" resource: "pods" args: "--all-namespaces" # Apply a configuration operation: "apply" resource: "" args: "-f deployment.yaml" # Drain a node (admin only) operation: "drain" resource: "node" args: "worker-1 --ignore-daemonsets" # Add a taint (admin only) operation: "taint" resource: "nodes" args: "worker-1 key=value:NoSchedule" ```
kubectl_workloads - Manage workload deployments **Available in**: readwrite, admin Manages deployment lifecycle operations including scaling and rollouts. **Parameters:** - `operation`: The operation to perform (run, expose, scale, autoscale, rollout) - `resource`: For rollout operations, the subcommand (status, history, undo, restart, pause, resume) - `args`: Additional arguments **Examples:** ```bash # Scale a deployment operation: "scale" resource: "deployment" args: "nginx --replicas=3" # Check rollout status operation: "rollout" resource: "status" args: "deployment/nginx" ```
kubectl_metadata - Manage resource metadata **Available in**: readwrite, admin Updates labels, annotations, and other metadata on resources. **Parameters:** - `operation`: The operation to perform (label, annotate, set) - `resource`: The resource type - `args`: Resource name and metadata changes **Examples:** ```bash # Add a label operation: "label" resource: "pods" args: "nginx-pod app=web" # Set image operation: "set" resource: "image" args: "deployment/nginx nginx=nginx:latest" ```
kubectl_diagnostics - Debug and monitor resources **Available in**: readonly, readwrite, admin Provides debugging and monitoring capabilities. **Parameters:** - `operation`: The operation to perform (logs, events, top, exec, cp) - `resource`: The resource type or specific resource - `args`: Additional arguments **Examples:** ```bash # View logs operation: "logs" resource: "" args: "nginx-pod -f" # Execute command in pod operation: "exec" resource: "" args: "nginx-pod -- ls /app" ```
kubectl_cluster - View cluster information **Available in**: readonly, readwrite, admin Provides cluster-level information and API discovery. **Parameters:** - `operation`: The operation to perform (cluster-info, api-resources, api-versions, explain) - `resource`: For explain operation, the resource to document - `args`: Additional flags **Examples:** ```bash # Get cluster info operation: "cluster-info" resource: "" args: "" # Explain pod spec operation: "explain" resource: "pod.spec" args: "--recursive" ```
kubectl_config - Configuration and security **Available in**: readonly, readwrite, admin Handles configuration validation, security operations, and kubectl context management. In readonly mode, supports `diff`, `auth can-i`, and read-only config operations. **Parameters:** - `operation`: The operation to perform (diff, auth, certificate, config) - `resource`: Subcommand for auth/certificate/config operations - `args`: Operation-specific arguments **Examples:** ```bash # Check permissions operation: "auth" resource: "can-i" args: "create pods" # Approve certificate operation: "certificate" resource: "approve" args: "csr-name" # Get current context operation: "config" resource: "current-context" args: "" # List all contexts operation: "config" resource: "get-contexts" args: "" # Switch context (readwrite/admin only) operation: "config" resource: "use-context" args: "my-cluster-context" ``` **Config Operations:** - `current-context`: Display the current context (readonly, readwrite, admin) - `get-contexts`: List all available contexts (readonly, readwrite, admin) - `use-context`: Switch to a different context (readwrite, admin only)
#### Additional Tools
call_helm - Helm package manager **Available when**: `--additional-tools=helm` is specified Run Helm commands for managing Kubernetes applications. **Parameters:** - `command`: The helm command to execute **Example:** ```bash command: "list --all-namespaces" ```
call_cilium - Cilium CNI commands **Available when**: `--additional-tools=cilium` is specified Run Cilium commands for network policies and observability. **Parameters:** - `command`: The cilium command to execute **Example:** ```bash command: "status" ```
call_hubble - Hubble observability commands **Available when**: `--additional-tools=hubble` is specified Run Hubble commands for network monitoring and debugging in Cilium-enabled clusters. **Parameters:** - `command`: The hubble command to execute **Example:** ```bash command: "status" command: "observe observe --namespace backend-jobs --from-label 'app=web'" command: "list nodes" ```
## Telemetry Telemetry collection is on by default. To opt out, set the environment variable `KUBERNETES_MCP_COLLECT_TELEMETRY=false`. ### OpenTelemetry Support The mcp-kubernetes server supports exporting telemetry data using OpenTelemetry Protocol (OTLP). You can configure an OTLP endpoint to send traces to any OpenTelemetry-compatible backend: ```json { "mcpServers": { "kubernetes": { "command": "mcp-kubernetes", "args": ["--otlp-endpoint", "localhost:4317"] } } } ``` ## Development How to inspect MCP server requests and responses: ```sh npx @modelcontextprotocol/inspector ``` ## Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. ## Trademarks This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.