"K3s" matching MCP servers:

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Model Context Protocol (MCP) server for debugging, analyzing, and diagnosing Kubernetes clusters directly from AI agents.

An MCP server that enables natural language querying and troubleshooting of Kubernetes clusters, supporting multi-cluster switching and providing tools for pods, nodes, events, and logs.

Gives AI assistants read-only access to a Kubernetes cluster's observability stack — Loki, Prometheus, Tempo, the Kubernetes API — plus AWS telemetry from CloudTrail, Config, ECR, and RDS. 23 tools for querying logs, metrics, traces, Kubernetes events, deployments, and audit history in plain language.

AI-powered Kubernetes diagnostics that analyzes pod crashes, logs, and cluster health to provide root cause analysis and actionable solutions for common issues like CrashLoopBackOff, OOM kills, and connection errors.

A read-only Kubernetes MCP server that enables developers to inspect app status, view pod events, and fetch container logs from dev clusters without requiring full kubectl access.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

Enables AI agents to inspect Kubernetes pods and cluster events, query Prometheus and Loki, and diagnose pod health with suggested actions through MCP tools.

Enables read-only Kubernetes cluster diagnostics through MCP tools, allowing a local LLM to inspect pods and events and debug issues via natural language queries.

A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.

Enables natural language Kubernetes operations, including smart resource queries, pod root-cause analysis, cross-environment diffs, and manifest generation.

A lightweight MCP server that enables AI assistants to deploy, inspect, and operate Kubernetes workloads through high-level workflow tools, reducing token usage with structured outputs.

Manage Your Kubernetes Cluster with k8s mcp-server

Enables AI assistants to diagnose Kubernetes clusters through read-only MCP tools, such as inspecting pod status, logs, events, nodes, deployments, and HPA metrics via natural language queries.

An MCP server for autonomous Kubernetes troubleshooting and remediation. It enables continuous cluster monitoring, local AI-powered diagnosis via Ollama, and automated kubectl-based fixes.

MCP server that filters Kubernetes warning/failure events and presents them to AI assistants for diagnostics. Enables AI to identify and troubleshoot cluster issues without consuming context on normal events.

Enables exploration of Kubernetes metrics, logs, traces, and service graph data via simple tools.

Enables read-only interaction with a Kubernetes cluster, allowing listing of nodes, pods, deployments, and services, as well as fetching pod logs.

Provides a read-only interface to Kubernetes clusters, enabling LLMs to list pods, get pod status and logs, fetch deployment manifests, and perform pod health analysis with resource trend tracking.

Provides read-only Kubernetes cluster operations via MCP, enabling LLMs to query nodes, pods, logs, events, and watch real-time status for troubleshooting.