Kubernetes Tools MCP Server
Related Servers
Alternatives to Kubernetes Tools MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceA read-only MCP server for inspecting Kubernetes clusters, allowing LLMs to list resources, describe pods, and read logs without mutation.5MIT
- FlicenseAqualityCmaintenanceRead-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.6-
- FlicenseNot gradedqualityBmaintenanceProvides read-only Kubernetes cluster operations via MCP, enabling LLMs to query nodes, pods, logs, events, and watch real-time status for troubleshooting.2-
- AlicenseAqualityDmaintenanceExposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.91MIT
- AlicenseNot gradedqualityDmaintenanceA read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.7MIT
- AlicenseAqualityBmaintenanceRead-only MCP server for safe Kubernetes inspection, diagnosis, and debugging. Supports Kubernetes core, Helm, Argo Workflows, and Argo CD.2391 npm5MIT
TDQS
Scored across 21 tools
Most tools target clearly distinct Kubernetes resources and levels (nodes, pods, deployments, services, logs, etc.), and the descriptions explicitly distinguish similar tools. However, get_pod_events overlaps with get_events, which can also filter by involved_kind and involved_name, creating a minor selection ambiguity.
All tool names use snake_case with a consistent get_ prefix and resource-oriented nouns. The patterns get_<resource>_summaries, get_<resource>, and get_logs_for_<entity> are predictable and easy to scan.
With 21 tools, the set is on the heavy side for a read-only inspection server. Many resource summaries are justified, but the surface could be consolidated (e.g. pod-specific events and generalized events, or separate job/cronjob log helpers).
Core workload inspection is well covered: pods, containers, logs, events, deployments, replica sets, stateful sets, daemon sets, jobs, cronjobs, services, configmaps, PVCs, nodes, and namespaces. Notable gaps remain for common Kubernetes resources such as ingresses, endpoints, secrets, storage classes, persistent volumes, HPA, and RBAC objects.