Kubernetes

MCP Server that can connect to a Kubernetes cluster and manage it. Supports loading kubeconfig from multiple sources in priority order. [https://github.com/user-attachments/assets/f25f8f4e-4d04-479b-9ae0-5dac452dd2ed Before using this MCP server with any tool, make sure you have: - kubectl installed and in your PATH - A valid kubeconfig file with contexts configured - Access to a Kubernetes cluster configured for kubectl (e.g. minikube, Rancher Desktop, GKE, etc.) - Helm v3 installed and in your PATH (no Tiller required). Optional if you don't plan to use Helm. You can verify your connection by running`kubectl get pods`in a terminal to ensure you can connect to your cluster without credential issues. By default, the server loads kubeconfig from`~/.kube/config`. For additional authentication options (environment variables, custom paths, etc.), see](https://github.com/user-attachments/assets/f25f8f4e-4d04-479b-9ae0-5dac452dd2ed)[ADVANCED_README.md. Add the MCP server to Claude Code using the built-in command: ``` `claude mcp add kubernetes -- npx mcp-server-kubernetes` ``` This will automatically configure the server in your Claude Code MCP settings. Add the MCP server to](https://github.com/Flux159/mcp-server-kubernetes/blob/HEAD/ADVANCED_README.md)[Codex CLIusing the built-in command: ``` `codex mcp add kubernetes -- npx mcp-server-kubernetes` ``` This registers the server globally in`~/.codex/config.toml`and makes its tools available in all Codex sessions. Add the following configuration to your Claude Desktop config file: ``` `{ "mcpServers": { "kubernetes": { "command": "npx", "args": ](https://developers.openai.com/codex/cli/)["mcp-server-kubernetes"] } } }` ``` MCP Server Kubernetes is also available as a[mcpb(formerly dxt) extension. In Claude Desktop, go to Settings (`Cmd+,`on Mac) -> Extensions -> Browse Extensions and scroll to find mcp-server-kubernetes in the modal. Install it & it will install & utilize kubectl via command line & your kubeconfig. To manually install, you can also get the .mcpb by going to the latest](https://github.com/anthropics/mcpb)[Releaseand downloading it. For VS Code integration, you can use the MCP server with extensions that support the Model Context Protocol: - Install a compatible MCP extension (such as Claude Dev or similar MCP clients) - Configure the extension to use this server: ``` `{ "mcpServers": { "kubernetes": { "command": "npx", "args": ](https://github.com/Flux159/mcp-server-kubernetes/releases)["mcp-server-kubernetes"], "description": "Kubernetes cluster management and operations" } } }` ``` Cursor supports MCP servers through its AI integration. Add the server to your Cursor MCP configuration: ``` `{ "mcpServers": { "kubernetes": { "command": "npx", "args": ["mcp-server-kubernetes"] } } }` ``` The server will automatically connect to your current kubectl context. You can verify the connection by asking the AI assistant to list your pods or create a test deployment. [mcp-chatis a CLI chat client for MCP servers. You can use it to interact with the Kubernetes server. ``` `npx mcp-chat --server "npx mcp-server-kubernetes"` ``` Alternatively, pass it your existing Claude Desktop configuration file from above (Linux should pass the correct path to config): ``` `npx mcp-chat --config "~/Library/Application Support/Claude/claude_desktop_config.json"` ``` ``` `npx mcp-chat --config "%APPDATA%\Claude\claude_desktop_config.json"` ``` - Connect to a Kubernetes cluster - Unified kubectl API for managing resources - Get or list resources with`kubectl_get` - Describe resources with`kubectl_describe` - List resources with`kubectl_get` - Create resources with`kubectl_create` - Apply YAML manifests with`kubectl_apply` - Delete resources with`kubectl_delete` - Get logs with`kubectl_logs` - Manage kubectl contexts with`kubectl_context` - Explain Kubernetes resources with`explain_resource` - List API resources with`list_api_resources` - Scale resources with`kubectl_scale` - Update field(s) of a resource with`kubectl_patch` - Manage deployment rollouts with`kubectl_rollout` - Execute any kubectl command with`kubectl_generic` - Verify connection with`ping` - Scale deployments with`kubectl_scale`(replaces legacy`scale_deployment`) - Port forward to pods and services with`port_forward` - Run Helm operations - Install, upgrade, and uninstall charts - Support for custom values, repositories, and versions - Template-based installation (`helm_template_apply`) to bypass authentication issues - Template-based uninstallation (`helm_template_uninstall`) to bypass authentication issues - Clean up problematic pods (`cleanup_pods`) in states: Evicted, ContainerStatusUnknown, Completed, Error, ImagePullBackOff, CrashLoopBackOff - Cordoning, draining, and uncordoning nodes (`node_management`) for maintenance and scaling operations - Guides through a systematic Kubernetes troubleshooting flow for pods based on a keyword and optional namespace. - Distributed tracing for all tool calls - Export to Jaeger, Tempo, Grafana, or any OTLP backend - Configurable sampling strategies - Rich span attributes (tool name, duration, K8s context, errors) - See](https://github.com/Flux159/mcp-chat)[docs/OBSERVABILITY.mdfor details The MCP Kubernetes server includes optional**OpenTelemetry integration**for comprehensive observability. This feature is disabled by default and can be enabled via environment variables or Helm configuration. Enable observability with environment variables: ``` `export ENABLE_TELEMETRY=true export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317 npx mcp-server-kubernetes` ``` - **All tool calls**: kubectl_get, kubectl_apply, kubectl_logs, etc. - **Execution duration**: How long each operation takes - **Success/failure status**: Automatic error tracking - **Kubernetes context**: Namespace, context, resource type - **Rich metadata**: Host, process, and custom attributes - **Jaeger**(open source) - **Grafana Tempo**(open source) - **Grafana Cloud**(commercial) - **Datadog**,**New Relic**,**Honeycomb**,**Lightstep**,**AWS X-Ray** See**](https://github.com/Flux159/mcp-server-kubernetes/blob/HEAD/docs/OBSERVABILITY.md)[docs/OBSERVABILITY.md**for comprehensive documentation including: - Configuration options - Deployment examples (Kubernetes, Helm, Claude Code) - Sampling strategies - Production best practices - Troubleshooting guide ``` `# Start Jaeger docker run -d --name jaeger \ -e COLLECTOR_OTLP_ENABLED=true \ -p 16686:16686 \ -p 4317:4317 \ jaegertracing/all-in-one:latest # Enable telemetry export ENABLE_TELEMETRY=true export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317 export OTEL_TRACES_SAMPLER=always_on # Run server npx mcp-server-kubernetes # View traces: http://localhost:16686` ``` The MCP Kubernetes server includes specialized prompts to assist with common diagnostic operations. This prompt provides a systematic troubleshooting flow for Kubernetes pods. It accepts a`keyword`to identify relevant pods and an optional`namespace`to narrow the search. The prompt's output will guide you through an autonomous troubleshooting flow, providing instructions for identifying issues, collecting evidence, and suggesting remediation steps. Make sure that you have](https://github.com/Flux159/mcp-server-kubernetes/blob/HEAD/docs/OBSERVABILITY.md)[bun installed. Clone the repo & install dependencies: ``` `git clone https://github.com/Flux159/mcp-server-kubernetes.git cd mcp-server-kubernetes bun install` ``` - Start the server in development mode (watches for file changes): ``` `npx @modelcontextprotocol/inspector node dist/index.js # Follow further instructions on terminal for Inspector link` ``` ``` `{ "mcpServers": { "mcp-server-kubernetes": { "command": "node", "args": ](https://bun.sh/docs/installation)["/path/to/your/mcp-server-kubernetes/dist/index.js"] } } }` ``` See the[CONTRIBUTING.mdfile for details. You can run the server in a non-destructive mode that disables all destructive operations (delete pods, delete deployments, delete namespaces, etc.): ``` `ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS=true npx mcp-server-kubernetes` ``` For Claude Desktop configuration with non-destructive mode: ``` `{ "mcpServers": { "kubernetes-readonly": { "command": "npx", "args": ](https://github.com/Flux159/mcp-server-kubernetes/blob/HEAD/CONTRIBUTING.md)["mcp-server-kubernetes"], "env": { "ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS": "true" } } } }` ``` ### Commands Available in Non-Destructive Mode All read-only and resource creation/update operations remain available: - Resource Information:`kubectl_get`,`kubectl_describe`,`kubectl_logs`,`explain_resource`,`list_api_resources` - Resource Creation/Modification:`kubectl_apply`,`kubectl_create`,`kubectl_scale`,`kubectl_patch`,`kubectl_rollout` - Helm Operations:`install_helm_chart`,`upgrade_helm_chart`,`helm_template_apply`,`helm_template_uninstall` - Connectivity:`port_forward`,`stop_port_forward` - Context Management:`kubectl_context` ### Commands Disabled in Non-Destructive Mode The following destructive operations are disabled: - `kubectl_delete`: Deleting any Kubernetes resources - `uninstall_helm_chart`: Uninstalling Helm charts - `cleanup`: Cleanup of managed resources - `cleanup_pods`: Cleaning up problematic pods - `node_management`: Node management operations (can drain nodes) - `kubectl_generic`: General kubectl command access (may include destructive operations) For additional advanced features, see the[ADVANCED_README.mdand also the](https://github.com/Flux159/mcp-server-kubernetes/blob/HEAD/ADVANCED_README.md)[docsfolder for specific information on`helm_install`,`helm_template_apply`, node management & pod cleanup. See this](https://github.com/Flux159/mcp-server-kubernetes/tree/main/docs)[DeepWiki linkfor a more indepth architecture overview created by Devin. This section describes the high-level architecture of the MCP Kubernetes server. The sequence diagram below illustrates how requests flow through the system: ``` `sequenceDiagram participant Client participant Transport as Transport Layer participant Server as MCP Server participant Filter as Tool Filter participant Handler as Request Handler participant K8sManager as KubernetesManager participant K8s as Kubernetes API Note over Transport: StdioTransport or<br>SSE Transport Client->>Transport: Send Request Transport->>Server: Forward Request alt Tools Request Server->>Filter: Filter available tools Note over Filter: Remove destructive tools<br>if in non-destructive mode Filter->>Handler: Route to tools handler alt kubectl operations Handler->>K8sManager: Execute kubectl operation K8sManager->>K8s: Make API call else Helm operations Handler->>K8sManager: Execute Helm operation K8sManager->>K8s: Make API call else Port Forward operations Handler->>K8sManager: Set up port forwarding K8sManager->>K8s: Make API call end K8s-->>K8sManager: Return result K8sManager-->>Handler: Process response Handler-->>Server: Return tool result else Resource Request Server->>Handler: Route to resource handler Handler->>K8sManager: Get resource data K8sManager->>K8s: Query API K8s-->>K8sManager: Return data K8sManager-->>Handler: Format response Handler-->>Server: Return resource data end Server-->>Transport: Send Response Transport-->>Client: Return Final Response` ``` See this](https://deepwiki.com/Flux159/mcp-server-kubernetes)[DeepWiki linkfor a more indepth architecture overview created by Devin. Go to the](https://deepwiki.com/Flux159/mcp-server-kubernetes)[releases page, click on "Draft New Release", click "Choose a tag" and create a new tag by typing out a new version number using "v{major}.{minor}.{patch}" semver format. Then, write a release title "Release v{major}.{minor}.{patch}" and description / changelog if necessary and click "Publish Release". This will create a new tag which will trigger a new release build via the cd.yml workflow. Once successful, the new release will be published to](https://github.com/Flux159/mcp-server-kubernetes/releases)[npm. Note that there is no need to update the package.json version manually, as the workflow will automatically update the version number in the package.json file & push a commit to main. If you find this repo useful, please cite: ``` `@software{Patel_MCP_Server_Kubernetes_2024, author = {Patel, Paras and Sonwalkar, Suyog}, month = jul, title = {{MCP Server Kubernetes}}, url = {https://github.com/Flux159/mcp-server-kubernetes}, version = {2.5.0}, year = {2024} }` ``` AniList MCP server for accessing AniList API data APISIX Model Context Protocol (MCP) server is used to bridge large language models (LLMs) with the APISIX Admin API, supporting querying and managing all resources in Apache APISIX. Get up-to-date EC2 pricing information with one call. Fast. Powered by a pre-parsed AWS pricing catalogue. Interact with your content on the Contentful platform A Model Context Protocol (MCP) server enabling interaction with Google Admin APIs. MCP server acting as an interface to the Google Ads, enabling programmatic access to Google Ads data and management features. Server for using HuggingFace Spaces, supporting Images, Audio, Text and more. Claude Desktop mode for ease-of-use. Golang-based Kubernetes MCP Server. Built to be extensible. A Python MCP server for Microsoft Entra ID (Azure AD) directory, user, group, device, sign-in, and security operations via Microsoft Graph. List and analyze Netbird network peers, groups, policies, and more.](https://www.npmjs.com/package/mcp-server-kubernetes)