Kubernetes Multi-Cluster Manager
Manages multiple Kubernetes clusters through a single interface, allowing you to run kubectl commands and access resources across different clusters without manually switching contexts.
Provides a bridge to Kubernetes multi-cluster environments for managing distributed resources through kubectl commands, service account connections, and seamless cross-cluster operations without switching contexts.
What it does
- List available Kubernetes clusters
- Connect to managed clusters with specified roles
- Execute kubectl commands across multiple clusters
- Apply YAML configurations to any cluster
- Retrieve resources from hub and managed clusters
Best for
About Kubernetes Multi-Cluster Manager
Kubernetes Multi-Cluster Manager is a community-built MCP server published by yanmxa that provides AI assistants with tools and capabilities via the Model Context Protocol. Kubernetes Multi-Cluster Manager enables seamless kubectl management across multiple clusters, connecting distributed re It is categorized under cloud infrastructure, developer tools. This server exposes 3 tools that AI clients can invoke during conversations and coding sessions.
How to install
You can install Kubernetes Multi-Cluster Manager in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Kubernetes Multi-Cluster Manager is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Tools (3)
Retrieves a list of Kubernetes clusters (also known as managed clusters or spoke clusters).
Generates the KUBECONFIG for the managed cluster and binds it to the specified ClusterRole (default: cluster-admin).
Securely run a kubectl command or apply YAML. Provide either 'command' or 'yaml'.
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
Mutiple Kubernetes Clusters Operations
📦 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.
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