What operations does the server support?
It supports EKS operations (list/describe clusters, nodegroups) and Kubernetes operations (list pods, deployments, services, get pod logs, etc.) via POST to `/mcp/v1/query`.
@mahmoudsalah84
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"eks-mcp-server-new": {
"command": "python",
"args": [
"main.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A lightweight server implementing the Model Context Protocol for EKS operations, providing a standardized interface for GenAI agents to interact with EKS clusters. It includes comprehensive EKS and Kubernetes resource management capabilities.
Run locally with Python (pip install -r requirements.txt, then python main.py) or with Docker (docker build -t eks-mcp-server . && docker run -d -p 8000:8000 --name mcp-server eks-mcp-server). Docker Compose (docker-compose up -d) and ECS deployment scripts are also provided. Tests are available via test_*.py scripts.
It supports EKS operations (list/describe clusters, nodegroups) and Kubernetes operations (list pods, deployments, services, get pod logs, etc.) via POST to `/mcp/v1/query`.
The server supports AWS SDK authentication, kubectl with generated kubeconfig, and direct Kubernetes API calls. The current implementation uses the kubectl method.
Docker (for containerized deployment) or Python 3.8+ (for local development), AWS credentials for production use, and ECS task role added to the EKS cluster’s aws-auth ConfigMap when deployed on ECS.
Deploy locally with Python/Docker, or to ECS using scripts in `ecs-deployment/`. The server is already deployed to ECS at `http://3.90.45.69:8000`.
Yes, a client implementation using Amazon Bedrock for conversational interaction is provided in the `client/` directory.
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