MCP Server for Kubernetes Support Bundles
Description
# MCP Server for Kubernetes Support Bundles [](LICENSE) [](https://www.python.org/downloads/) A Model Context Protocol (MCP) server for AI models…
About
# MCP Server for Kubernetes Support Bundles [](LICENSE) [](https://www.python.org/downloads/) A Model Context Protocol (MCP) server for AI models to interact with Kubernetes support…
Details
- Author
- chris-sanders
- GitHub stars
- 1
- Downloads
- 249
- Categories
- Cloud Service
Jump to
- Bundle management: initialize and manage support bundles
- Execute kubectl commands against the bundle’s API server
- Navigate, search, and read files within the bundle
- Token‑based authentication for secure access
- Containerized deployment with Podman (development and production variants)
- Single Bundle Mode for ephemeral/serverless environments
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP Server for Kubernetes Support BundlesCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Run the server with Podman or install manually with Python 3.13 and UV. Set the authentication token via the SBCTL_TOKEN environment variable. For stateless deployments, enable Single Bundle Mode with MCP_SINGLE_BUNDLE_MODE=true and PRESERVE_BUNDLES=true. Invoke tools like initialize_bundle, kubectl, list_files, read_file, and grep_files over the MCP protocol.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp server for kubernetes support bundles": {
"troubleshoot-mcp-server": {
"command": "uv",
"args": [
"venv",
"-p",
"python3.13",
".venv"
]
}
}
}
}McpServers
{
"troubleshoot-mcp-server": {
"command": "uv",
"args": [
"venv",
"-p",
"python3.13",
".venv"
]
}
}MCP Server for Kubernetes Support Bundles
A Model Context Protocol (MCP) server for AI models to interact with Kubernetes support bundles. This server enables AI models to analyze and troubleshoot Kubernetes clusters by exploring support bundles generated by the Troubleshoot tool.
Features
- 🚀 Bundle Management: Initialize and manage Kubernetes support bundles
- 🎮 Command Execution: Run kubectl commands against bundle's API server
- 📁 File Explorer: Navigate and search files within the bundle
- 🔐 Secure Authentication: Token-based authentication for bundle access
- 🐳 Container Support: Run as a containerized application
- ⚡ Single Bundle Mode: Stateless operation for ephemeral/serverless deployments
Single Bundle Mode (Stateless Operation)
For stateless/ephemeral deployments (Temporal workflows, serverless functions, container-per-request architectures), enable Single Bundle Mode:
export MCP_SINGLE_BUNDLE_MODE=true
export PRESERVE_BUNDLES=true
export MCP_BUNDLE_STORAGE=/persistent-storage/bundles
What is Single Bundle Mode?
Single Bundle Mode eliminates in-memory bundle state tracking by treating the presence of a bundle on disk as the source of truth. This enables:
- Automatic Bundle Restoration: When the server starts, it auto-activates the bundle persisted on disk
- Stateless Server Restarts: Each server restart automatically uses the persisted bundle without re-initialization
- Single Bundle Invariant: Only one bundle can exist at a time, preventing state confusion
- Seamless Temporal/Serverless Integration: Works perfectly with short-lived server instances
Usage Pattern
```bash
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