"Cloud Foundry" matching MCP servers:

Wraps multiple cloud CLIs (AWS, GCP, Azure, OCI) into a unified command interface and exposes them as MCP tools for AI assistants.

Unified MCP server for managing cloud resources across AWS, Google Cloud, Azure, and DigitalOcean by wrapping their CLI tools.

Enables interaction with Google Cloud Platform services through gcloud CLI commands via a Cloud Run deployed MCP server. Supports executing gcloud commands and managing GCP resources through natural language.

A cloud replacement for mcp-server-filesystem that provides 30 tools for S3, Azure Blob, and Google Cloud Storage, deployable locally via STDIO or remotely over HTTP/WebSocket with OAuth 2.1 authentication.

Enables a coding-agent session to exchange messages with another machine's session over SSH, returning replies and maintaining per-peer conversation history across calls without a cloud relay or extra API keys.

Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.

Geniuz stores everything in a local database locally on Mac, Windows, Linux, Raspberry Pi. No cloud. No account. No API keys. Nothing leaves your machine. It's open source; you can read every line of code.

MCP server for controlling local music playback via NetEase Cloud Music, enabling search, play, pause, skip, and lyrics display through a local web player.

Enables MCP clients such as Claude and Cursor to control an isolated cloud machine with a real browser, shell, filesystem, and web access, so agents can navigate pages, click and type, run commands, manage files, and search or fetch web content.

An MCP server that enables Claude to interact with Tembo Cloud platform API, allowing users to manage Tembo Cloud resources through natural language.

Gives MCP-compatible AI agents a full local terminal over stdio, enabling shell command execution, file reads and writes, content search, background processes, and stateful tmux sessions with variable capture, auditing, and a configurable command denylist. Requires no deployment or cloud setup.

An MCP server that lets AI agents manage virtual machines across local and cloud targets, with tools to create machines, run commands, transfer files, and clean up ephemeral instances via natural language.

An MCP server that exposes the Huawei Cloud CLI as a single tool for AI assistants to discover and execute commands interactively via --help navigation, with built-in safety for destructive operations.

Enables AI agents to fetch Nebius cloud service documentation and execute Nebius CLI commands for managing cloud resources like compute instances and storage buckets through natural language interactions.

A secure, local communication runtime bridge that interfaces a cloud-based Large Language Model (Claude Desktop) with a local machine execution environment using the Model Context Protocol (MCP).

A remote Streamable HTTP MCP server that lets web clients like Claude.ai and ChatGPT manage cloud machines with OAuth login — creating, starting, pausing and deleting machines, running commands, reading and writing files, managing snapshots and public ports, and driving an optional Linux desktop via screenshots and input actions. Long-running work can be backgrounded and operations polled, so browser-based clients stay within their timeouts.

Enables cloud AI agents to safely work on a Mac through MCP-style JSON-RPC by providing approval-gated command execution, jailed file access, signed requests, and a tamper-evident audit log. Risky actions require on-device approval, while files remain confined to a chosen folder with recoverable writes and deletions.

Enables local AI clients on Windows to automate desktop and system tasks via MCP stdio, CLI, or optional localhost HTTP, including screenshots, mouse and keyboard input, files, processes, registry, and accessibility-tree window interactions, with local-only execution and no cloud fallback.

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

Enables local load testing with k6/locust/native tools and cloud-based test management through the perfscale platform.