This is an MCP kubernetes Server.
MCP Kubernetes Server MCP server exists for a simple reason — assistants are far more useful when they can act on MCP Kubernetes Server directly instead of describing what you should do. This is an MCP kubernetes Server.
This is an MCP (Model Context Protocol) server for Kubernetes that provides control over Kubernetes clusters through interactions with LLMs.
This client allows you to perform common Kubernetes operations through MCP tools. It wraps kubectl commands to provide a simple interface for managing Kubernetes resources. The Model Context Protocol (MCP) enables seamless interaction between language models and Kubernetes operations.
Once MCP Kubernetes Server is connected, these are the calls the assistant has available:
port — forward pod,deployment,service with name in the production namespace to local port 8080The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
kubectl - Python 3.x - MCP framework installed and configuredThis sits in the cloud and infrastructure group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MCP Kubernetes Server's toolset — port — is a fair guide to whether it matches your workflow. It is maintained by abhijeetka; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against MCP Kubernetes Server's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| port | forward pod,deployment,service with name <resource-name> in the production namespace to local port 8080. |
{
"mcpServers": {
"Kubernetes": {
"command": "uv",
"args": [
"--directory",
"~/mcp/mcp-k8s-server",
"run",
"kubernetes.py"
]
}
}
}Configuration as documented by the project. Restart the client after saving.
kubectl - Python 3.x - MCP framework installed and configuredManage your whole Supabase project in conversation — database, auth, storage, Edge Functions and branches.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
AWS Labs' official server suite — current AWS docs, CDK guidance, cost analysis and service tools.
Cloud browsers for AI agents — automation sessions that run in Browserbase's fleet, not on your machine.
Workers, KV, R2 and D1 by conversation — Cloudflare's official remote servers for building and observability.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.