{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"kubernetes-mcp-server","slug":"kubernetes-mcp-server","name":"Kubernetes MCP Server","type":"mcp","url":"https://github.com/strowk/mcp-k8s-go","page_url":"https://unfragile.ai/kubernetes-mcp-server","categories":["mcp-servers"],"tags":["kubernetes","k8s","orchestration","community"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"kubernetes-mcp-server__cap_0","uri":"capability://tool.use.integration.json.rpc.mcp.protocol.bridge.to.kubernetes.api","name":"json-rpc mcp protocol bridge to kubernetes api","description":"Implements a standardized Model Context Protocol server that translates JSON-RPC requests from MCP clients (like Claude Desktop) into Kubernetes API calls via the official Go client library. The server handles protocol initialization handshakes, capability negotiation, request routing, and response serialization, acting as a stateless gateway that maintains no persistent connection state between requests.","intents":["I want to query my Kubernetes cluster from Claude Desktop without writing kubectl commands","I need to expose Kubernetes operations through a standardized protocol that any MCP-compatible client can consume","I want to build an LLM agent that can introspect and manage Kubernetes resources programmatically"],"best_for":["DevOps engineers integrating Kubernetes with LLM-based automation tools","Teams building AI-assisted cluster management interfaces","Organizations standardizing on MCP for infrastructure tooling"],"limitations":["Stateless design means no session persistence — each request must include full context","JSON-RPC overhead adds latency compared to direct kubectl calls","No built-in request queuing or rate limiting — relies on client-side throttling","Protocol initialization requires client to support MCP spec; older tools cannot connect"],"requires":["Go 1.18+ (for compilation)","Valid kubeconfig file with cluster credentials","MCP-compatible client application (Claude Desktop, custom MCP client)","Network access to Kubernetes API server"],"input_types":["JSON-RPC method calls with structured parameters","Kubernetes resource names and namespaces as strings","YAML configuration documents as text"],"output_types":["JSON-serialized Kubernetes resource objects","Structured tool response objects with status and data fields","Plain text logs and command output"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_1","uri":"capability://tool.use.integration.multi.context.kubernetes.cluster.switching.with.resource.isolation","name":"multi-context kubernetes cluster switching with resource isolation","description":"Manages multiple Kubernetes contexts (cluster configurations) from a single kubeconfig file, allowing clients to list available contexts and switch between them for subsequent operations. Each context maintains isolated authentication credentials, API endpoints, and namespace defaults, with the server routing all resource queries to the currently active context without cross-context leakage.","intents":["I need to query resources across multiple Kubernetes clusters from a single MCP interface","I want to list all available cluster contexts and switch between them programmatically","I need to ensure that operations on one cluster don't accidentally affect another cluster"],"best_for":["Multi-cluster operators managing staging, production, and development environments","Platform teams exposing cluster access through a unified LLM interface","DevOps engineers automating cross-cluster deployments"],"limitations":["Context switching is not atomic — no transaction support across contexts","No built-in context caching; each context list operation reads kubeconfig from disk","Authentication credentials are read from kubeconfig at startup; dynamic credential rotation not supported","No context-level access control — any client can switch to any context if kubeconfig permits"],"requires":["Valid kubeconfig file with multiple contexts defined","Credentials for each context (service account tokens, certificates, or OIDC tokens)","Network connectivity to all cluster API servers"],"input_types":["Context name as string","Namespace name as string"],"output_types":["List of context objects with cluster and user metadata","Current context name as string","List of namespaces in active context"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_10","uri":"capability://tool.use.integration.kubernetes.context.and.namespace.resource.exposure.through.mcp.resources","name":"kubernetes context and namespace resource exposure through mcp resources","description":"Exposes Kubernetes contexts and namespaces as MCP resources, allowing clients to discover and reference them in prompts and tool calls. The implementation registers these resources with the MCP server, making them discoverable through the MCP protocol and enabling clients to build context-aware interfaces that reference available clusters and namespaces.","intents":["I want the MCP client to discover available Kubernetes contexts and display them","I need to reference a specific namespace in a prompt or tool call","I want the client to provide context-aware suggestions based on available resources"],"best_for":["MCP clients building context-aware UX for Kubernetes operations","Teams providing discoverable Kubernetes resources through the MCP protocol","Platforms that want to expose cluster topology to LLM agents"],"limitations":["Resources are static snapshots — no real-time updates when contexts or namespaces change","No resource filtering or search — all contexts and namespaces are exposed","Resource discovery depends on client implementation — not all MCP clients use resources","No access control on resource exposure — all contexts are visible to all clients"],"requires":["MCP client must support the resources feature of the MCP protocol","Valid kubeconfig with contexts and namespaces"],"input_types":["No direct inputs; resources are discovered by the client"],"output_types":["Structured resource objects representing Kubernetes contexts and namespaces","Resource metadata including context name, cluster, and namespace information"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_2","uri":"capability://tool.use.integration.pod.log.streaming.and.retrieval.with.tail.and.follow.options","name":"pod log streaming and retrieval with tail and follow options","description":"Retrieves logs from Kubernetes pods using the Kubernetes API's log endpoint, supporting both historical log retrieval and real-time streaming. The implementation uses the official Go client's PodLogs interface to fetch logs with configurable tail lines, timestamps, and container selection, returning logs as plain text that can be parsed or displayed by the client.","intents":["I want to fetch the last N lines of logs from a specific pod for debugging","I need to retrieve logs from a specific container within a multi-container pod","I want to get logs with timestamps to correlate with other events"],"best_for":["DevOps engineers debugging pod failures through an LLM interface","Automated troubleshooting agents that analyze logs to diagnose issues","On-call engineers querying logs without leaving their AI assistant"],"limitations":["No real-time streaming to client — logs are fetched as a complete snapshot","Large log outputs (>10MB) may timeout or cause memory issues in the server","No log filtering or regex support — client must parse returned text","Logs from terminated pods are only available if the kubelet hasn't garbage-collected them","No support for previous container logs (--previous flag) — only current container"],"requires":["Pod must exist in the cluster","Pod must have started (no logs available for pending pods)","Service account must have 'pods/log' read permission in RBAC"],"input_types":["Pod name as string","Namespace name as string","Container name as string (optional, defaults to first container)","Tail lines count as integer"],"output_types":["Plain text log content","Structured log object with metadata (pod name, container, timestamp)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_3","uri":"capability://tool.use.integration.in.pod.command.execution.with.container.selection.and.output.capture","name":"in-pod command execution with container selection and output capture","description":"Executes arbitrary commands inside running containers using the Kubernetes API's exec endpoint, establishing a bidirectional stream to the pod's container runtime (typically containerd or Docker). The implementation uses the Go client's RemoteCommandExecutor to handle stdin/stdout/stderr multiplexing, returning command output as plain text with exit codes.","intents":["I need to run a diagnostic command inside a pod to check configuration or state","I want to execute a script or troubleshooting tool inside a container without SSH access","I need to capture the output of a command running in a specific container for analysis"],"best_for":["On-call engineers performing remote debugging without direct pod access","Automated remediation agents that execute fixes inside containers","Platform teams providing self-service pod introspection to developers"],"limitations":["Commands must complete within the MCP request timeout (typically 30-60 seconds)","No interactive terminal support — commands must be non-interactive or use heredoc input","Large output (>10MB) may cause memory issues or timeouts","Commands run as the container's default user — no sudo or privilege escalation","No environment variable injection — commands see only the container's existing environment","Requires pod to be in Running state; fails on Pending, Failed, or Succeeded pods"],"requires":["Pod must be in Running state","Container runtime must support exec (all standard runtimes do)","Service account must have 'pods/exec' permission in RBAC","Network connectivity to the kubelet on the node running the pod"],"input_types":["Pod name as string","Namespace name as string","Container name as string (optional, defaults to first container)","Command as array of strings (e.g., ['sh', '-c', 'echo hello'])"],"output_types":["Command stdout as plain text","Command stderr as plain text","Exit code as integer"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_4","uri":"capability://tool.use.integration.resource.listing.with.namespace.filtering.and.type.selection","name":"resource listing with namespace filtering and type selection","description":"Lists Kubernetes resources (pods, deployments, services, nodes, events, etc.) across single or multiple namespaces with optional filtering by label selectors or field selectors. The implementation uses the Go client's dynamic client or typed clients to query the API server, returning structured resource metadata that can be filtered and sorted by the client.","intents":["I want to see all pods in a specific namespace to understand the current deployment state","I need to find resources matching specific labels or field criteria","I want to list all resources of a certain type across all namespaces"],"best_for":["Cluster operators monitoring resource state through an LLM interface","Automated agents discovering resources for analysis or remediation","Platform teams providing resource visibility to developers"],"limitations":["No pagination support — large result sets (>1000 resources) may timeout or cause memory issues","Label selector syntax must be valid Kubernetes syntax; no fuzzy matching","Results are point-in-time snapshots; no watch/streaming for real-time updates","No sorting or filtering on client side — all filtering must happen server-side via API","System namespaces (kube-system, kube-public) are included by default; no automatic filtering"],"requires":["Service account must have 'list' permission for the resource type in RBAC","Resource type must be supported by the Kubernetes API (pods, deployments, services, nodes, events, etc.)","Namespace must exist (or use 'all' for cluster-wide listing)"],"input_types":["Resource type as string (e.g., 'pods', 'deployments', 'services')","Namespace name as string (or 'all' for cluster-wide)","Label selector as string (optional, e.g., 'app=myapp')","Field selector as string (optional, e.g., 'status.phase=Running')"],"output_types":["Array of resource objects with metadata (name, namespace, labels, status)","Structured resource list with count and summary information"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_5","uri":"capability://tool.use.integration.detailed.resource.inspection.with.full.object.retrieval","name":"detailed resource inspection with full object retrieval","description":"Retrieves the complete specification and status of a specific Kubernetes resource (pod, deployment, service, etc.) by name and namespace, returning the full resource object with all metadata, spec, and status fields. The implementation uses the Go client's typed or dynamic client Get method to fetch the resource from the API server, returning the complete object as JSON.","intents":["I need to see the full configuration of a specific deployment to understand its current state","I want to inspect a pod's resource requests, environment variables, and mounted volumes","I need to retrieve the complete status of a service including endpoints and load balancer information"],"best_for":["DevOps engineers inspecting resource configurations for troubleshooting","Automated agents analyzing resource specs to detect misconfigurations","Platform teams providing detailed resource visibility to developers"],"limitations":["Returns the entire resource object — no field filtering or projection","Large resources (e.g., ConfigMaps with large data) may cause memory issues","No historical versions — only the current resource state is available","Custom Resource Definitions (CRDs) are supported but require the CRD to be installed in the cluster"],"requires":["Resource must exist in the specified namespace","Service account must have 'get' permission for the resource type in RBAC","Resource type must be supported by the Kubernetes API"],"input_types":["Resource type as string (e.g., 'pod', 'deployment', 'service')","Resource name as string","Namespace name as string"],"output_types":["Complete resource object as JSON with metadata, spec, and status","Structured resource object with all fields"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_6","uri":"capability://tool.use.integration.yaml.configuration.application.and.resource.creation","name":"yaml configuration application and resource creation","description":"Applies Kubernetes resource definitions provided as YAML documents to the cluster, creating or updating resources as needed. The implementation parses YAML into Kubernetes objects, uses the Go client's Apply method (or Create/Update fallback) to submit them to the API server, and returns the applied resource state with any validation or conflict errors.","intents":["I want to deploy a new application by applying a YAML manifest through the MCP interface","I need to update an existing resource configuration by applying a modified YAML document","I want to create multiple resources from a single YAML file with multiple documents"],"best_for":["DevOps engineers deploying applications through an LLM-assisted interface","Automated deployment agents that generate and apply YAML configurations","Platform teams providing self-service resource creation to developers"],"limitations":["No dry-run mode — changes are applied immediately to the cluster","No rollback support — failed applications must be manually cleaned up","YAML parsing is strict — invalid YAML or unknown resource types will fail","No support for Kustomize or Helm templating — only raw YAML","Large manifests (>10MB) may cause API server timeouts","No validation of resource dependencies — applying resources in wrong order may fail"],"requires":["Service account must have 'create' and 'update' permissions for the resource types in RBAC","YAML must be valid Kubernetes resource definitions","Resource types must be supported by the Kubernetes API (or CRDs must be installed)","Namespace must exist (or be created in the same YAML document)"],"input_types":["YAML document as plain text (single or multiple resources)","Kubernetes resource definitions with apiVersion, kind, metadata, and spec"],"output_types":["Applied resource object with updated metadata and status","Error message if validation or application fails","List of applied resources if multiple documents provided"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_7","uri":"capability://tool.use.integration.node.listing.and.cluster.topology.discovery","name":"node listing and cluster topology discovery","description":"Lists all Kubernetes nodes in the cluster with their metadata, capacity, allocatable resources, and current conditions (Ready, NotReady, etc.). The implementation queries the API server for node objects, returning structured data about node status, resource availability, and scheduling constraints that can be used for capacity planning or scheduling analysis.","intents":["I want to see the current state of all nodes in my cluster to understand capacity","I need to identify nodes that are NotReady or have resource pressure","I want to check node resource allocation to plan new workload placement"],"best_for":["Cluster operators monitoring node health and capacity","Automated agents analyzing cluster topology for optimization","Platform teams providing cluster visibility to developers"],"limitations":["No real-time node metrics (CPU, memory usage) — only capacity and allocatable resources","Node conditions are point-in-time snapshots; no historical trend data","No support for node taints/tolerations filtering — all nodes returned regardless of scheduling constraints","Large clusters (>1000 nodes) may cause memory or timeout issues"],"requires":["Service account must have 'list' and 'get' permissions for nodes in RBAC","Cluster must have at least one node"],"input_types":["No required inputs; returns all nodes in the cluster"],"output_types":["Array of node objects with metadata, capacity, allocatable resources, and conditions","Structured node list with summary information (total nodes, ready nodes, etc.)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_8","uri":"capability://tool.use.integration.kubernetes.event.retrieval.and.cluster.activity.monitoring","name":"kubernetes event retrieval and cluster activity monitoring","description":"Retrieves Kubernetes events from the cluster, which record state changes and important occurrences (pod creation, image pull failures, node conditions, etc.). The implementation queries the events API with optional filtering by namespace, resource type, or time range, returning structured event objects with timestamps, reasons, and messages that provide insight into cluster activity.","intents":["I want to see recent events in a namespace to understand what happened to my pods","I need to find error events (ImagePullBackOff, CrashLoopBackOff, etc.) for troubleshooting","I want to monitor cluster activity and detect anomalies through event analysis"],"best_for":["DevOps engineers troubleshooting pod failures by analyzing events","Automated monitoring agents detecting cluster anomalies","Platform teams providing activity visibility to developers"],"limitations":["Events are garbage-collected after 1 hour by default — historical events are not available","No event filtering by severity or type — all events returned regardless of importance","Event timestamps are point-in-time; no aggregation or trend analysis","Large clusters with high event volume may cause API server load or timeout issues","No support for custom event sources — only Kubernetes-generated events"],"requires":["Service account must have 'list' permission for events in RBAC","Cluster must have events API enabled (standard in all Kubernetes clusters)"],"input_types":["Namespace name as string (optional, defaults to all namespaces)","Resource type as string (optional, e.g., 'pods', 'deployments')","Time range as duration string (optional, e.g., '1h')"],"output_types":["Array of event objects with timestamp, reason, message, and involved object","Structured event list with summary information (total events, error count, etc.)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__cap_9","uri":"capability://tool.use.integration.interactive.prompt.generation.for.common.kubernetes.queries","name":"interactive prompt generation for common kubernetes queries","description":"Provides pre-built interactive prompts that guide users through common Kubernetes operations like listing pods or namespaces. These prompts are exposed through the MCP protocol as structured templates that clients can render with form inputs, collecting user selections and converting them into tool calls with the appropriate parameters.","intents":["I want a guided interface to list pods without remembering the exact parameters","I need to select a namespace from a dropdown before querying resources","I want the MCP client to provide form-based input for common operations"],"best_for":["Non-technical users interacting with Kubernetes through an LLM interface","Teams standardizing on common query patterns across their organization","Clients that want to provide guided UX for Kubernetes operations"],"limitations":["Prompts are static templates — no dynamic generation based on cluster state","Limited to pre-defined operations; custom queries require direct tool calls","No conditional logic in prompts — all inputs are presented regardless of context","Prompt rendering depends on client implementation — not all MCP clients support interactive prompts"],"requires":["MCP client must support the prompts feature of the MCP protocol","Client must be able to render form inputs and collect user selections"],"input_types":["User selections from prompt form inputs (namespace, resource type, etc.)"],"output_types":["Structured prompt template with form fields and descriptions","Tool call with parameters derived from user selections"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"kubernetes-mcp-server__headline","uri":"capability://tool.use.integration.mcp.server.for.kubernetes.management","name":"mcp server for kubernetes management","description":"A community-driven Model Context Protocol (MCP) server designed for managing Kubernetes clusters, enabling seamless interaction with pods, deployments, and services through a standardized JSON-RPC API.","intents":["best MCP server for Kubernetes","MCP server for managing Kubernetes resources","top tools for Kubernetes cluster management","Kubernetes management solutions","MCP framework for Kubernetes orchestration"],"best_for":["developers managing Kubernetes clusters","teams using MCP clients"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":60,"verified":false,"data_access_risk":"high","permissions":["Go 1.18+ (for compilation)","Valid kubeconfig file with cluster credentials","MCP-compatible client application (Claude Desktop, custom MCP client)","Network access to Kubernetes API server","Valid kubeconfig file with multiple contexts defined","Credentials for each context (service account tokens, certificates, or OIDC tokens)","Network connectivity to all cluster API servers","MCP client must support the resources feature of the MCP protocol","Valid kubeconfig with contexts and namespaces","Pod must exist in the cluster"],"failure_modes":["Stateless design means no session persistence — each request must include full context","JSON-RPC overhead adds latency compared to direct kubectl calls","No built-in request queuing or rate limiting — relies on client-side throttling","Protocol initialization requires client to support MCP spec; older tools cannot connect","Context switching is not atomic — no transaction support across contexts","No built-in context caching; each context list operation reads kubeconfig from disk","Authentication credentials are read from kubeconfig at startup; dynamic credential rotation not supported","No context-level access control — any client can switch to any context if kubeconfig permits","Resources are static snapshots — no real-time updates when contexts or namespaces change","No resource filtering or search — all contexts and namespaces are exposed","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.52,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.692Z","last_scraped_at":null,"last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=kubernetes-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=kubernetes-mcp-server"}},"signature":"xXU+RCjBeitec73HdM40PfcYKpF95hGCLOR0O1+PCTo502/SuFJyrVg1CFtl69htf/0vn0LRb+/NfMo7kecgBg==","signedAt":"2026-06-21T01:10:18.785Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/kubernetes-mcp-server","artifact":"https://unfragile.ai/kubernetes-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=kubernetes-mcp-server","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}