Virtualization, Servers and Storage : ITS Private Cloud Model Context Protocol (MCP) Server

A Model Context Protocol server for seamless AI integration with University of Toronto's ITS Private Cloud Virtual Server Service

What is Model Context Protocol?

The Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to external data sources and tools. Think of it as a universal translator that allows AI models to:

• Access Real-time Data: Connect to live systems and databases

• Execute Actions: Perform operations like creating snapshots or managing VMs

• Maintain Context: Keep track of resources and relationships across conversations

• Ensure Security: Authenticate and authorize access to sensitive systems

With MCP, your AI assistant becomes a powerful interface to your cloud infrastructure, capable of understanding complex queries like "Show me the most expensive VMs this month and suggest cost optimizations" or "Create a snapshot of vm-server before the maintenance window."

See it in action

Getting Started

📋Prerequisites

• Python 3.10 or higher

• ITS Private Cloud VSS API access token

• MCP-compatible AI client (Claude Desktop, etc.)

⚡Installation

Using vss-cli

1. Upgrade to version 2025.6.0

   1. brew update && brew upgrade vss-cli

2. Configure the vss-cli with: vss-cli configure mk

3. Run vss-cli mcp install

Using uvx

1. Install uv from Astral or the GitHub README

2. Install Python using uv python install 3.10

3. Run with uvx mcp-vss

Using pip

1. Install python 3.13 with brew or any other method:

   brew install python@3.13

2. Create a venv with

   python3 -m venv .venv && source .venv/bin/activate && python3 -m pip install --upgrade pip

3. Install with pip install mcp-vss

⚙️Configuration

Add the server to your MCP client configuration:

{ 
 "mcpServers": { 
   "its-private-cloud": { 
     "command": "/full/path/to/python", 
     "args": ["-m", "mcp_server_vss"], 
     "env": { 
       "MCP_VSS_API_TOKEN": "your-api-token-here" 
     } 
   } 
 } 
}

Workflows

🖥️Virtual Machine Management

• VM Discovery: Find VMs by name, ID, or properties

• Health Monitoring: Check VM status, performance, and resource utilization

• Snapshot Management: Create point-in-time backups before changes

• Power Control: Start, stop, restart, or suspend virtual machines

• Console Access: Get emergency console links for troubleshooting

💰Cost Analysis & Optimization

• Billing Analysis: Review invoices and identify cost drivers

• Resource Rightsizing: Find overprovisioned or idle resources

• Trend Analysis: Track spending patterns over time

• Optimization Reports: Get actionable recommendations to reduce costs

🔍Performance Monitoring

• Real-time Metrics: Monitor CPU, memory, disk, and network usage

• Trend Analysis: Identify performance patterns and bottlenecks

• Capacity Planning: Forecast resource needs based on historical data

• Alerting: Get notifications about performance issues

🛠️Infrastructure Operations

• Backup Analysis: Monitor UTORrecover backup sessions and data usage

• Network Management: View available networks and configurations

• OS Catalog: Browse supported operating systems for deployments

• Domain Management: Monitor compute clusters and resource allocation

🎯Troubleshooting & Support

• Diagnostic Workflows: Automated troubleshooting guides

• Issue Resolution: Step-by-step problem-solving assistance

• Performance Tuning: Optimization recommendations based on metrics

• Change Management: Safe deployment practices with snapshot integration

Available Tools

🖥️Virtual Machine Tools

💰Billing & Cost Management Tools

🔒Backup & Data Management Tools

Available Prompts

📊Performance Analysis

💸Cost & Financial Analysis

Available Resources

🏗️Infrastructure Resources

💼Billing Resources