rohitg00/kubectl-mcp-server

A Model Context Protocol (MCP) server for Kubernetes, enabling AI assistants (like Claude, Cursor, Windsurf) to interact with Kubernetes clusters using natural language via the MCP protocol.

Source: GitHub - rohitg00/kubectl-mcp-server

Category: cloud-devops-mcp-servers

Tags: mcp, kubernetes, cloud-native, ai-integration

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Features

Core Kubernetes Operations

• Connect to a Kubernetes cluster
• List and manage pods, services, deployments, and nodes
• Create, delete, and describe pods and other resources
• Get pod logs and Kubernetes events
• Support for Helm v3 operations (install, upgrade, uninstall)
• kubectl explain and api-resources support
• Choose namespace for next commands (memory persistence)
• Port forward to pods
• Scale deployments and statefulsets
• Execute commands in containers
• Manage ConfigMaps and Secrets
• Rollback deployments to previous versions
• Ingress and NetworkPolicy management
• Context switching between clusters

Natural Language Processing

• Process natural language queries for kubectl operations
• Context-aware commands with memory of previous operations
• Human-friendly explanations of Kubernetes concepts
• Intelligent command construction from intent
• Fallback to kubectl when specialized tools aren't available
• Mock data support for offline/testing scenarios
• Namespace-aware query handling

Monitoring

• Cluster health monitoring
• Resource utilization tracking
• Pod status and health checks
• Event monitoring and alerting
• Node capacity and allocation analysis
• Historical performance tracking
• Resource usage statistics via kubectl top
• Container readiness and liveness tracking

Security

• RBAC validation and verification
• Security context auditing
• Secure connections to Kubernetes API
• Credentials management
• Network policy assessment
• Container security scanning
• Security best practices enforcement
• Role and ClusterRole management
• ServiceAccount creation and binding
• PodSecurityPolicy analysis
• RBAC permissions auditing
• Security context validation

Diagnostics

• Cluster diagnostics and troubleshooting
• Configuration validation
• Error analysis and recovery suggestions
• Connection status monitoring
• Log analysis and pattern detection
• Resource constraint identification
• Pod health check diagnostics
• Common error pattern identification
• Resource validation for misconfigurations
• Detailed liveness and readiness probe validation

Advanced Features

• Multiple transport protocols support (stdio, SSE, HTTP)
• Integration with multiple AI assistants
• Extensible tool framework
• Custom resource definition (CRD) support
• Cross-namespace operations
• Batch operations on multiple resources
• Intelligent resource relationship mapping
• Error explanation with recovery suggestions
• Volume management and identification

Architecture & Operation

• Implements the Model Context Protocol (MCP) for standardized AI-Kubernetes interaction
• MCP server handles requests from AI assistants
• Tools registry for Kubernetes operations exposed as MCP tools
• Transport layer supports stdio, SSE, and HTTP
• CLI mode and server mode supported
• Response formatter for MCP-compliant responses

Installation

• Installable via PyPI: pip install kubectl-mcp-tool
• Python 3.9+, kubectl CLI, access to Kubernetes cluster required
• Supports global and local development installation
• Includes installation script for automatic configuration with supported AI assistants

Usage

• Designed to run as an MCP server for AI tools (not a direct kubectl replacement)
• Integration guides for Claude, Cursor, and Windsurf
• Provides configuration templates for each assistant
• Example commands for listing pods, deploying apps, checking logs, port forwarding

Development

• Includes comprehensive test suite for core, security, monitoring, NLP, diagnostics
• Modular project structure for easy contribution and extension

Known Issues

• JSON parsing issues are currently being debugged for some AI assistants (Claude, Cursor, Windsurf)

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Pricing

• Open Source: Free to use under the MIT License. No paid plans.

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License

• MIT License

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Contributors

• Rohit Ghumare
• Ian Moroney
• Sajeeva Lakmal

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