MCP Kubernetes Server

v1.0.0

Community

MCPkubernetesorchestrationmcpmodel-context-protocol
76
Strong
About This MCP

Community-maintained MCP server for Kubernetes cluster management. Enables AI models to interact with Kubernetes API for pod management, deployment orchestration, service configuration, and cluster resource monitoring. Essential for AI-powered Kubernetes operations and cloud-native application management.

Last Evaluated: November 9, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+
k8s api reliability

API stability analysis

Evidence
Kubernetes API — Built on stable Kubernetes API with mature implementation
highVerified: 2025-11-09
resource operation success

Operation success testing

Evidence
Kubernetes MCP Server — High success rate for pod, deployment, and service operations
highVerified: 2025-11-09
cluster state accuracy

State synchronization testing

Evidence
Kubernetes Watch API — Accurate real-time cluster state tracking
highVerified: 2025-11-09
multi cluster performance

Multi-cluster performance testing

Evidence
Implementation Review — Performance varies with cluster size and network latency
mediumVerified: 2025-11-09
error recovery

Error handling testing

Evidence
Implementation Review — Handles Kubernetes API errors with retry and reconciliation
mediumVerified: 2025-11-09
🛡️Security
+
rbac enforcement

Authorization testing

Evidence
Kubernetes RBAC — Respects Kubernetes RBAC but requires careful role configuration
highVerified: 2025-11-09
kubeconfig exposure risk

Credential security analysis

Evidence
MCP Security Model — Kubeconfig credentials stored locally; AI has cluster access
highVerified: 2025-11-09
destructive operation risk

Operation risk assessment

Evidence
Security Analysis — AI can delete pods, deployments, and modify cluster resources
highVerified: 2025-11-09
namespace isolation

Isolation boundary testing

Evidence
Kubernetes Namespaces — Namespace isolation depends on RBAC configuration
mediumVerified: 2025-11-09
secret access risk

Secrets management assessment

Evidence
Kubernetes Secrets — Can access Kubernetes secrets if RBAC permits
highVerified: 2025-11-09
audit logging

Audit logging review

Evidence
Kubernetes Audit Logs — All API operations logged in Kubernetes audit system
highVerified: 2025-11-09
🔒Privacy & Compliance
+
cluster metadata exposure

Data flow analysis

Evidence
MCP Data Flow — Cluster configurations, pod specs, and resource metadata sent to LLM
highVerified: 2025-11-09
pod log privacy

Log privacy assessment

Evidence
Privacy Analysis — Pod logs may contain sensitive application data
highVerified: 2025-11-09
secret exposure risk

Secret privacy assessment

Evidence
Security Analysis — Kubernetes secrets accessible if RBAC permits
mediumVerified: 2025-11-09
third party data sharing

Data sharing analysis

Evidence
LLM Provider Policies — Cluster data shared with LLM provider per their privacy policy
highVerified: 2025-11-09
configmap data privacy

Configuration privacy assessment

Evidence
Kubernetes ConfigMaps — ConfigMaps may contain sensitive configuration data
mediumVerified: 2025-11-09
👁️Trust & Transparency
+
documentation quality

Documentation completeness review

Evidence
Kubernetes MCP Docs — Good documentation but community-maintained with evolving coverage
mediumVerified: 2025-11-09
operation visibility

Logging and traceability assessment

Evidence
Kubernetes Audit Logs — All operations logged in Kubernetes audit trail and MCP logs
highVerified: 2025-11-09
open source transparency

Source code review

Evidence
GitHub Repository — Open source community implementation
highVerified: 2025-11-09
security best practices

Security documentation review

Evidence
Security Documentation — Limited security guidance for production deployments
mediumVerified: 2025-11-09
⚙️Operational Excellence
+
ease of setup

Setup complexity assessment

Evidence
Setup Documentation — Requires kubeconfig setup and appropriate RBAC configuration
mediumVerified: 2025-11-09
api performance

Performance benchmarking

Evidence
Kubernetes API Performance — Performance depends on cluster size and network (typically 100-500ms)
mediumVerified: 2025-11-09
reliability

Reliability analysis

Evidence
Kubernetes Stability — Built on mature Kubernetes API with high reliability
highVerified: 2025-11-09
resource coverage

Feature coverage assessment

Evidence
Kubernetes MCP Server — Covers pods, deployments, services, configmaps, and secrets
highVerified: 2025-11-09
community support

Community support assessment

Evidence
GitHub Community — Community-maintained with moderate activity and support
mediumVerified: 2025-11-09
Strengths
  • +Comprehensive Kubernetes resource management and orchestration
  • +Built on stable and mature Kubernetes API
  • +Excellent for cloud-native application deployment automation
  • +Full operation auditability through Kubernetes audit logs
  • +Open source community implementation
  • +Supports RBAC for granular access control
Limitations
  • !Cluster configurations and pod specs exposed to LLM provider
  • !AI can delete resources and modify critical cluster configurations
  • !Pod logs and Kubernetes secrets accessible if RBAC permits
  • !Requires careful RBAC configuration to limit access
  • !Community-maintained with variable support quality
  • !ConfigMaps and secrets may contain sensitive data
Metadata
license: MIT
supported platforms
0: All platforms with kubectl
programming languages
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers
api dependency: Kubernetes API
authentication: kubeconfig, Service Account tokens
first release: 2024-11
maintained by: Community

Use Case Ratings

code generation

Excellent for Kubernetes manifest generation and GitOps automation

customer support

Good for troubleshooting Kubernetes deployments and cluster issues

content creation

Limited applicability; mainly for infrastructure documentation

data analysis

Good for analyzing cluster metrics, resource utilization, and scaling patterns

research assistant

Useful for researching Kubernetes patterns and cluster configurations

legal compliance

High risk due to cluster access; requires strict RBAC controls

healthcare

Risk of exposing healthcare infrastructure; not recommended without strong controls

financial analysis

Moderate risk for financial infrastructure management

education

Excellent for teaching Kubernetes, container orchestration, and cloud-native architecture

creative writing

Low relevance to creative writing workflows