Multi-Cloud VM MCP Server

Multi-Cloud VM MCP Server is an MCP server that enables AI clients to manage and inspect virtual machines across major cloud platforms. It establishes connections to Amazon Web Services, Microsoft Azure, and Google Cloud Platform to interface directly with AWS EC2, Azure Virtual Machines, and GCP Compute Engine instances. DevOps engineers, cloud architects, and systems administrators use this server to supervise compute resources through conversational prompts without manually logging into multiple cloud management consoles. By exposing unified cloud compute endpoints to large language model agents, the server enables users to retrieve compute information, monitor instance availability, and control virtual machine operations across distributed environments. Users can coordinate instances across hybrid-cloud setups, compare infrastructure state, and centralize infrastructure oversight through standard Model Context Protocol client workflows.

Category: Cloud & Infrastructure

Tags: aws, azure, compute, gcp, virtual-machines

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How to install and configure Multi-Cloud VM MCP Server

1. Clone the repository locally: bash git clone https://github.com/neelabalan/cloud-compute-mcp-server.git ~/cloud-compute-mcp-server 2. Open your MCP client configuration file (such as Claude Desktop or Cursor). 3. Add the following entry to your mcpServers configuration block: json { "mcpServers": { "CloudComputeInfo": { "command": "~/.local/bin/uv", "args": [ "run", "--with", "mcp[cli]", "--with", "requests", "--with", "pyyaml", "mcp", "run", "~/cloud-compute-mcp-server/main.py" ] } } } 4. Save the configuration and restart your MCP client.

What you can do with Multi-Cloud VM MCP Server

• Querying running compute instances across AWS EC2, Azure Virtual Machines, and GCP Compute Engine within a unified prompt. - Checking resource statuses and configurations for multi-cloud deployments without navigating multiple provider web consoles. - Automating cross-cloud virtual machine inspection workflows through conversational AI assistants during operational incident triage. - Standardizing compute management routines for cloud teams operating distributed infrastructure across multiple enterprise providers.

Key facts

• https://github.com/neelabalan/cloud-compute-mcp-server
• Cloud & Infrastructure
• aws, azure, compute, gcp, virtual-machines

Part of MCP Servers

How do I install Multi-Cloud VM MCP Server?

You can install Multi-Cloud VM MCP Server by cloning the project repository to your local directory and configuring your MCP client to execute it. Use the uv package runner to run the main.py script with required dependencies including mcp[cli], requests, and pyyaml as defined in the server configuration block.

What can Multi-Cloud VM MCP Server do?

Multi-Cloud VM MCP Server manages and queries virtual machines across different cloud environments. It connects AI assistants directly to AWS EC2, Azure Virtual Machines, and GCP Compute Engine, letting users inspect VM metadata, track instance states, and coordinate cloud compute resources from an AI interface.

Which MCP clients work with Multi-Cloud VM MCP Server?

Multi-Cloud VM MCP Server works with any client that implements the standard Model Context Protocol. This includes desktop environments like Claude Desktop, AI code editors like Cursor, and custom command-line or orchestration agents capable of launching local sub-processes via standard input and output.

What cloud platforms does Multi-Cloud VM MCP Server support?

The server provides integration for three primary cloud providers: Amazon Web Services (AWS EC2), Microsoft Azure (Azure Virtual Machines), and Google Cloud Platform (GCP Compute Engine).