"Information about Microsoft Azure cloud platform" matching MCP servers:

Enables MCP-capable clients to inventory and operate Azure resources via the Azure Resource Manager API, including resource groups, tags, and VM power, while enforcing governance controls like scoping, protected groups, location allowlists, delete gating, and confirmation.

Manages and views virtual machines across multiple cloud providers (AWS, Azure, Alibaba Cloud). Enables AI assistants to list, inspect, and control VMs through a unified MCP interface.

An MCP server for interacting with Azure. Contains some common Compute and Networking actions, and extensible to add many more.

MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.

Provides tools for interacting with Azure services including Storage, Virtual Machines, and App Service operations.

Enables monitoring and management of Azure resources including Virtual Machines (VMs) and Virtual Machine Scale Sets (VMSS) through a RESTful API with secure Service Principal authentication.

Enables management of Verda Cloud GPU instances through Claude, allowing users to deploy spot instances, attach volumes, and monitor status. It supports automated workflows for checking availability and configuring instances with startup scripts.

MCP server for managing Yandex Cloud infrastructure including Compute VMs, Object Storage, Serverless Functions, and Operations.

Open-source MCP server for managing Hetzner Cloud infrastructure with two management layers: * Layer 1 — Hetzner Cloud API (35 tools): Server power control, metrics, snapshots, backups, firewalls, DNS zones and records, rescue mode, server rebuild and rescale. Works even when the server OS is unresponsive. * Layer 2 — SSH (25 tools): Service management (systemd), Nginx config and reload,

Provides ChatGPT with a persistent, VM-like Linux engineering workstation inside Docker, with root access, development tools, and a private nested Docker daemon.

Enables users to list GKE clusters, describe virtual machines, and retrieve billing information through MCP read tools, without applying production changes.

Enables deploying multiple isolated Odoo MCP connector containers from a single shared codebase, each with its own configuration and credentials for different clients.

Enables managing Akamai Cloud (Linode) Compute Instances via MCP, with tools to list, create, view, update, delete, boot, reboot, shutdown, resize, and clone VMs. Each connecting client brings its own Linode Personal Access Token, which is passed through without being stored.

An MCP server implementation that enables AI assistants to interact with and manage Sakura Cloud infrastructure, including servers, disks, networks, and containerized applications.

Read-only MCP server for Yandex Cloud resources including VMs, networks, disks, and more, with support for cloud/organization level access.

A Model Context Protocol server for managing cloud servers, particularly DigitalOcean droplets, allowing users to identify providers via IP addresses and perform operations like power management, status monitoring, and resource usage tracking.

An AI-powered containerization assistant that helps you build, scan, and deploy Docker containers through VS Code and other MCP-compatible tools.

Enables LLMs to manage and monitor Hetzner Cloud infrastructure, including servers, firewalls, networks, and snapshots, while keeping the API token local and secure.

Persistent, secure LXC sandbox environments for AI agents with native MCP support.

Enables users to query Azure HPC/AI Kubernetes clusters for GPU node information and InfiniBand topology details through kubectl commands. Provides tools to list GPU pool nodes with their status and retrieve network topology labels for high-performance computing workloads.