Open Cluster Management MCP Server

What is Open Cluster Management MCP Server about?

Enables Generative AI agents to query, retrieve, and analyze resources across a hub cluster and its managed clusters, leveraging Open Cluster Management to handle multi‑cluster environments.

How to use Open Cluster Management MCP Server?

Add the server to your MCP configuration:

{
  "mcpServers": {
    "multicluster-mcp-server": {
      "command": "npx",
      "args": ["-y", "multicluster-mcp-server@latest"]
    }
  }
}

Ensure kubectl is installed and the KUBECONFIG environment variable points to the hub cluster. The tool will use this hub context to reach managed clusters.

Key features

• Retrieve resources from the hub cluster (current context).
• Retrieve resources from managed clusters.
• Connect to a managed cluster using a specified ClusterRole.
• Access resources across multiple Kubernetes clusters via Open Cluster Management.
• Retrieve and analyze metrics, logs, and alerts from integrated clusters.
• Prompt templates tailored for Open Cluster Management tasks.
• References to official OCM documentation for development and integration.

Use cases

• Allow AI agents to read and reason about workloads spread over many clusters.
• Centralized observability for multi‑cluster environments (metrics, logs, alerts).
• Automate policy, add‑on, and resource management through reusable prompt templates.
• Support AI‑driven troubleshooting, capacity planning, and decision‑making across clusters.

FAQ

Q: What are the prerequisites? A: kubectl must be installed and KUBECONFIG set to the hub cluster.

Q: Can the server modify resources? A: Current focus is on read‑only operations and observability; write capabilities are planned.

Q: How do I specify a managed cluster? A: Use the provided CLI options or configure a ClusterRole for the target cluster as described in the documentation.

Q: Is the project open source? A: Yes, it is released under the MIT License.

Open Cluster Management MCP Server

The OCM MCP Server provides a robust gateway for Generative AI (GenAI) systems to interact with multiple Kubernetes clusters through the Model Context Protocol (MCP). It facilitates comprehensive operations on Kubernetes resources, streamlined multi-cluster management, and delivered interactive cluster observability.

🚀 Features

🛠️ MCP Tools - Kubernetes Cluster Awareness

• ✅ Retrieve resources from the hub cluster (current context)

• ✅ Retrieve resources from the managed clusters

• ✅ Connect to a managed cluster using a specified ClusterRole

• ✅ Access resources across multiple Kubernetes clusters(via Open Cluster Management)

• 🔄 Retrieve and analyze metrics, logs, and alerts from integrated clusters

• ❌ Interact with multi-cluster APIs, including Managed Clusters, Policies, Add-ons, and more

  

  

📦 Prompt Templates for Open Cluster Management (Planning)

• Provide reusable prompt templates tailored for OCM tasks, streamlining agent interaction and automation

📚 MCP Resources for Open Cluster Management (Planning)

• Reference official OCM documentation and related resources to support development and integration

📌 How to Use

Configure the server using the following snippet:

{
  "mcpServers": {
    "multicluster-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "multicluster-mcp-server@latest"
      ]
    }
  }
}

Note: Ensure kubectl is installed. By default, the tool uses the KUBECONFIG environment variable to access the cluster. In a multi-cluster setup, it treats the configured cluster as the hub cluster, accessing others through it.

License

This project is licensed under the MIT License.