Intelligent MCP server for Kubernetes resource exploration, relationship mapping, and debugging with AI-powered insights
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"k8s-explorer-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# 🔍 K8s Explorer MCP > An intelligent MCP server for Kubernetes resource exploration, relationship mapping, and debugging. Understands CRDs, provides AI-powered insights, and optimizes responses for LLM consumption. [](https://www.python.org/downloads/) [](LICENSE) [](https://gofastmcp.com) ## ✨ Features - 🔍 **Intelligent Resource Discovery** - Find ConfigMaps/Secrets a pod uses, detect Helm charts, trace operator management - 🌳 **Relationship Mapping** - Complete parent-child chains, service routing, volume mounts - 📦 **13+ CRD Operators** - Helm, ArgoCD, Airflow, Argo Workflows, Knative, FluxCD, Istio, cert-manager, Tekton, Spark, KEDA, Velero, Prometheus + AI-powered fallback for unknown CRDs - ⚡ **Smart Caching** - 4-layer cache with 80%+ hit rate for fast repeated queries - 🎯 **Response Filtering** - 70-90% smaller responses optimized for LLM consumption - 🔒 **Permission-Aware** - Adapts to RBAC constraints with helpful explanations - 🤖 **AI-Powered Insights** - Natural language explanations using FastMCP sampling - 📝 **Built-in Prompt** - Pre-configured debugging workflow prompt - 🔄 **Multi-Cluster Support** - Seamless switching between multiple K8s contexts ## 🚀 Quick Start ### Prerequisites - Python 3.10 or higher - kubectl configured with access to a Kubernetes cluster - Git ### Installation ```bash # Install from PyPI (recommended) uv pip install k8s-explorer-mcp # Or install from source git clone https://github.com/nirwo/k8s-explorer-mcp.git cd k8s-explorer-mcp uv pip install -e ".[dev]" ``` ### MCP Configuration Add to your Cursor MCP configuration (`~/.cursor/mcp.json`): ```json { "mcpServers": { "k8s-explorer": { "command": "uv", "args": [ "--directory", "/path/to/k8s-explorer-mcp", "run", …
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.