1. Create [kube-config](https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig/) for accessing kubernetes cluster. 2.
MCP K8s connects MCP K8s to AI assistants that speak the Model Context Protocol. 1. Create kube-config for accessing kubernetes cluster. 2. Build a docker image using Dockerfile. docker build . -t mcp:0.0.1.
docker build . -t mcp:0.0.1Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
{
"mcpServers": {
"k8s-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"mcp:0.0.1",
"uv",
"run",
"src/main.py"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
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.
kubectl with a conversational interface — inspect pods, read logs, diagnose clusters and manage workloads.