What are the prerequisites?
AWS CLI configured, Docker installed, Terraform >= 1.0, kubectl installed, and an AWS account with an existing ECR repository.
@jbrcoleman
基本情報
Demo eks mcp server
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp-server-eks-jbrcoleman": {
"command": "python",
"args": [
"server-enhanced.py"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
This project deploys a Model Context Protocol (MCP) server on Amazon EKS using Terraform for infrastructure management. It provides natural-language and programmatic access to Kubernetes cluster operations, targeting developers and platform teams who manage AWS EKS clusters.
Deploy via the provided scripts in phases (infrastructure, Karpenter, app) or all at once using ./scripts/deploy.sh all. For legacy deployment without Karpenter, use make init plan apply then make deploy. Local testing is possible with python server-enhanced.py after installing dependencies. Integrate with Claude Desktop by copying the claude-desktop-config.json to the appropriate configuration path.
get_cluster_status, list_pods, get_deploymentsAWS CLI configured, Docker installed, Terraform >= 1.0, kubectl installed, and an AWS account with an existing ECR repository.
Run `./scripts/deploy.sh all` for a single-command deployment, or deploy in phases: `./scripts/deploy.sh infrastructure`, then `./scripts/deploy.sh karpenter`, then `./scripts/deploy.sh app`.
Use `kubectl get service mcp-server-service -n mcp-server` to access the service and `kubectl logs -f deployment/mcp-server -n mcp-server` to view logs.
For Karpenter deployments, remove resources in reverse order: `kubectl delete -f k8s/`, then destroy Karpenter Terraform, then the main Terraform. For legacy deployments, use `make destroy` (not explicitly shown but implied by cleanup section).
Karpenter provides Kubernetes-native node autoscaling with a NodePool and EC2NodeClass, configuring instance types (t3.medium/large/xlarge), capacity types (spot/on-demand), and cost optimization by preferring spot instances.
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Model Context Protocol Servers
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