k8s-explorer-mcp 0.1.3

Intelligent MCP server for Kubernetes resource exploration, relationship mapping, and debugging with AI-powered insights

🔍 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.

✨ 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

# 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):

{
  "mcpServers": {
    "k8s-explorer": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/k8s-explorer-mcp",
        "run",
        "server.py"
      ],
      "env": {
        "PYTHONUNBUFFERED": "1"
      }
    }
  }
}

Replace /path/to/k8s-explorer-mcp with your actual project path.

As Python Library

from k8s_explorer import K8sClient, K8sCache, RelationshipDiscovery
import asyncio

async def main():
    cache = K8sCache(resource_ttl=60, max_size=2000)
    client = K8sClient(cache=cache)
    discovery = RelationshipDiscovery(client)
    
    # Get a resource
    pods = await client.list_resources(
        kind="Pod",
        namespace="default",
        label_selector="app=nginx"
    )
    
    # Discover relationships
    if pods:
        relationships = await discovery.discover_relationships(pods[0])
        for rel in relationships:
            print(f"{rel.relationship_type}: {rel.target.kind}/{rel.target.name}")
    
    # Build resource tree
    from k8s_explorer.models import ResourceIdentifier
    resource_id = ResourceIdentifier(kind="Deployment", name="nginx", namespace="default")
    tree = await discovery.build_resource_tree(resource_id, max_depth=3)
    
    stats = client.get_cache_stats()
    print(f"Cache hit rate: {stats['hit_rate_percent']}%")

asyncio.run(main())

As MCP Server

# Start the server
uv run server.py

# Or with make
make run

Available Tools (9 streamlined tools):

Core Operations (4)

• list_contexts() - List available contexts and accessible namespaces
• list_resources(kind, namespace, labels, all_namespaces) - Generic list any resource type
• get_resource(kind, name, namespace) - Get specific resource (smart matching for Pods)
• kubectl(args, namespace) - Execute kubectl commands for flexibility

Discovery (1)

• discover_resource(kind, name, namespace, depth="complete") - ONE tool for all discovery needs
  • depth="relationships": Fast list of connections (owners, children, volumes, CRDs)
  • depth="tree": Hierarchical tree structure showing resource hierarchy
  • depth="complete": Full context for debugging (default) - includes management info, explanations
  • Replaces 3 separate tools with clear depth parameter

Logs (1)

• get_pod_logs(name, namespace, container, previous, tail, timestamps) - Get pod logs
  • Optimized for LLM consumption
  • Automatically handles multi-container pods
  • Shows truncation info and available containers

Change Tracking (2)

• get_resource_changes(kind, name, namespace, max_versions) - Timeline of changes

  • Shows what changed between versions
  • LLM controls depth with max_versions

• compare_resource_versions(kind, name, namespace, from_revision, to_revision) - Version comparison

  • Detailed field-by-field comparison

Graph Analysis (1)

• build_resource_graph(namespace, kind, name, depth, include_rbac, include_network, include_crds) - Build complete resource graph
  • Two modes: specific resource or full namespace
  • Incremental graph building with caching
  • RBAC, Network Policy, and CRD relationship support

Built-in Prompt (1)

• debug_failing_pod(pod_name, namespace) - Complete debugging workflow for failing pods with guided investigation steps

All tools and prompts are permission-aware and will:

• Adapt responses based on your RBAC permissions
• Include permission notices when access is limited
• Provide clear guidance on missing permissions

🎯 What Can We Discover?

✅ Everything Your LLM Needs for K8s Operations

ConfigMaps & Secrets: Automatically finds all config resources a pod uses (volume mounts, env vars, projected volumes)

Helm Charts: Detects which Helm chart created any resource (release name, chart version, all managed resources)

Operators (13+): Identifies resources managed by Helm, ArgoCD, Argo Workflows, Airflow, Knative, FluxCD, Istio, cert-manager, Tekton, Spark, KEDA, Velero, Prometheus + AI-powered fallback for unknown CRDs

Complete Relationships: Parent-child chains, service routing, volume dependencies, label selectors, operator management

📚 Documentation

Document	Description
agents.md	Comprehensive agent guide
CONTRIBUTING.md	How to contribute
examples/	Usage examples

📦 Project Structure

k8s-explorer-mcp/
├── server.py                 # MCP server
├── k8s_explorer/             # Main package
│   ├── client.py             # Kubernetes client wrapper
│   ├── cache.py              # Multi-layer caching
│   ├── config.py             # Configuration system
│   ├── models.py             # Data models
│   └── operators/            # CRD operator support
├── examples/                 # Usage examples
├── tests/                    # Test suite
└── pyproject.toml            # Project metadata

🎯 Use Cases

🧠 Smart Pod Matching (NEW)

# Pod was recreated with different suffix? No problem!
get_resource("Pod", "myapp-deployment-abc123-old999", "default")

# Automatically finds and returns:
# {
#   "name": "myapp-deployment-def456-xyz789",
#   "match_info": {
#     "fuzzy_match_used": true,
#     "original_name": "myapp-deployment-abc123-old999",
#     "matched_name": "myapp-deployment-def456-xyz789",
#     "similarity_score": 1.0,
#     "match_reason": "exact_base_match",
#     "explanation": "Pod 'myapp-deployment-abc123-old999' not found, but found 
#                     'myapp-deployment-def456-xyz789' with same base name 
#                     'myapp-deployment'. This is likely a newer instance."
#   }
# }

# Search for pods by pattern (fuzzy matching built-in)
get_resource("Pod", "cronjob-backup", "default")

# Automatically finds similar pods with similarity scores
# Handles: Deployments, StatefulSets, Jobs, CronJobs suffixes

🐛 Debugging Made Easy

# Get complete context for debugging (smart matching included)
discover_resource("Pod", "my-app-xyz", "production", depth="complete")

# Returns:
# - ConfigMaps it needs (and if they exist)
# - Secrets it uses (with mount details)
# - Parent Deployment/ReplicaSet
# - Helm chart managing it
# - Complete failure context with explanations
# - Match info if pod name was fuzzy matched

# Get pod logs (with automatic container detection)
get_pod_logs("my-app-xyz", "production", tail=200)

# Returns:
# - Logs from the pod (auto-detects single container)
# - Pod status and container list
# - Truncation info
# - Match info if fuzzy matching was used

📊 Change Tracking & Investigation (NEW)

# What changed in the last deployment?
get_resource_changes("Deployment", "nginx-deployment", "production", max_versions=3)

# Returns:
# {
#   "latest_changes": {
#     "from_revision": "5",
#     "to_revision": "6",
#     "summary": "2 field(s) modified",
#     "changes": [
#       {
#         "field": "spec.replicas",
#         "change_type": "modified",
#         "old_value": "3",
#         "new_value": "5",
#         "delta": 2,
#         "percent_change": 66.67
#       },
#       {
#         "field": "spec.template.spec.containers[0].image",
#         "change_type": "modified",
#         "old_value": "nginx:1.21",
#         "new_value": "nginx:1.22"
#       }
#     ]
#   },
#   "timeline": [...],  # History of all changes
#   "note": "Use max_versions to control how far back to look"
# }

# Compare specific versions
compare_resource_versions("Deployment", "nginx", "prod", from_revision=3, to_revision=5)

# Get full change history (defaults to last 5 versions)
get_resource_changes("Deployment", "nginx", "prod")
# Returns: Timeline of changes with diffs

🔍 Impact Analysis

# What will break if I delete this ConfigMap?
discover_resource("ConfigMap", "app-config", "prod", depth="tree")

# Shows:
# - All Deployments using it
# - All ReplicaSets affected
# - All Pods that will restart

# Quick check of dependencies
discover_resource("Secret", "db-password", "prod", depth="relationships")
# Fast list of all resources using this secret

🚀 Operator Debugging

# Debug Airflow DAG - find related resources
list_resources("Pod", "airflow", labels={"dag_id": "etl-pipeline"})

# Debug Argo Workflow - full context
discover_resource("Workflow", "data-processing", "workflows", depth="complete")

# Debug Helm release - shows chart, version, all managed resources
discover_resource("Deployment", "nginx", "default", depth="complete")
# Returns: Helm release name, chart version, all related resources

🤖 LLM-Powered Operations

The LLM can now understand:

• "Show me all pods created by the nginx Helm chart"
• "What ConfigMaps does this deployment use?"
• "Why is my Airflow task failing?"
• "What will break if I update this Secret?"

All with one tool call and complete context!

🧪 Running Tests

# Run all tests
make test

# Run with coverage report
make test-cov

# Run specific test file
pytest tests/test_cache.py

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

# Install with dev dependencies
make install-dev

# Format code
make format

# Lint code
make lint

# Run all checks
make check

📝 License

MIT License - see LICENSE file for details.

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Made with ❤️ for the Kubernetes community