"Clever Cloud" matching MCP servers:

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.

Enables MCP-aware agents to read and explore Oracle Cloud Infrastructure — listing, fetching, and searching across 39 resource types spanning Identity, Compute, Block Volume, Networking, Object Storage, and OKE. Runs locally over stdio using credentials from ~/.oci/config, with fail-closed safety gates and audit logging governing future write operations.

An MCP server implementation that integrates with the Civo cloud platform API, providing capabilities to manage cloud instances, networks, and Kubernetes clusters.

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.

Enables managing Hostkey .ru cloud account resources via natural language, including servers, ordering, power control, OS reinstall, networking, DNS, snapshots, and billing.

Enables managing Hostkey cloud resources including servers, catalog, power, OS reinstall, network, DNS, snapshots, IPMI, ISO, S3, Remote Hands, billing, and API keys through natural language.

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

Enables AI assistants to provision and manage cloud infrastructure and AI/ML workloads—such as GPUs, nodes, storage, networking, databases, Kubernetes, and training/inference resources—through natural language. It also provides a universal REST tool for authenticated access to the underlying cloud API.

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 the Hetzner Cloud API that enables natural language management of cloud infrastructure. Users can list, create, and modify servers, networks, volumes, and load balancers through MCP-compatible clients.

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.

Enables agents to deploy, run, expose, inspect, and manage isolated cloud environments, including databases, caches, browsers, GitHub-hosted apps, and arbitrary OCI images, via MCP tools.

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,

An MCP server for Kvindo Cloud that lets AI clients list, inspect, create, update, and delete cloud resources (VMs, volumes, Kubernetes, etc.) via natural language. Read-only by default, with write/delete operations gated by explicit opt-in environment variables.

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.

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 interaction with Google Kubernetes Engine (GKE) to list clusters, manage node pools, and retrieve server configurations. It includes automated scripts for deploying and testing sample applications across multiple GKE Autopilot clusters.