by reza-gholizade · MCP Server · ★ 167
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Kubernetes MCP Server A Kubernetes Model Context Protocol (MCP) server that provides tools for interacting with Kubernetes clusters through a standardized interface. Features API Resource Discovery: Get all available API resources in your Kubernetes cluster. Resource Listing: List resources of any type with optional namespace and label filtering. Resource Details: Get detailed information about specific Kubernetes resources. Resource Description: Get comprehensive descriptions of Kubernetes resources, similar to . Pod Logs: Retrieve logs from specific pods (optionally from a specific container, or all containers if unspecified). Node Metrics: Get resource usage metrics for specific nodes. Pod Metrics: Get CPU and Memory metrics for specific pods. Event Listing: List events within a namespace or for a specific resource. Resource Creation/Updating: Create new Kubernetes resources or update existing ones from a YAML or JSON manifest. Resource Deletion: It deletes a resource in the Kubernetes cluster based on the provided namespace and kind. Standardized Interface: Uses the MCP protocol for consistent tool interaction.
| Stars | 167 |
| Forks | 42 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 59.82/100 |
| Last Updated | 2026-06-15 |
| Created | 2025-04-13 |
| Platforms | go, k8s, mcp |
| Est. Tokens | ~23k |
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k8s-mcp-server is Manage Your Kubernetes Cluster with k8s mcp-server. It is categorized as a MCP Server with 167 GitHub stars.
k8s-mcp-server is primarily written in Go. It covers topics such as ai, ai-agents, golang.
You can find installation instructions and usage details in the k8s-mcp-server GitHub repository at github.com/reza-gholizade/k8s-mcp-server. The project has 167 stars and 42 forks, indicating an active community.
k8s-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to k8s-mcp-server on Agent Skills Hub include yokai, golf, context-space. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.