"How to Read an Excel File" matching MCP servers:

Connects MCP-compatible coding agents to VMware vCenter to query information about virtual machines, hosts, clusters, datastores, datacenters, and networks.

DockaShell is an MCP server that provides AI agents with isolated Docker containers for persistent shell access, file operations, and full audit trails, enabling autonomous development and self-evolving workflows.

Enables AI agents to operate disposable Linux computers via MCP, providing tools for shell, file read/write, directory listing, and port exposure. It also supports browser automation and integration with any MCP-compatible client.

Enables AI agents to manage and interact with Kasm Workspaces containerized desktop infrastructure, providing tools for session management, command execution, file operations, and user management via the Model Context Protocol.

MCP server for building and driving VMware Workstation VMs from an AI agent, enabling unattended OS installs, guest command execution, file transfer, screenshots, and fleet management.

A Python-based server that enables AI assistants to interact with an Unraid server through the official Unraid GraphQL API, providing read-only access to system information, Docker containers, VMs, storage, and more.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

Enables an AI assistant to read container logs and server metrics and, after confirmation, start/stop/restart whitelisted containers on an Unraid server via a restricted API, with audit logging and no root access.

MCP server and CLI for host and container operations, enabling Docker and Compose control, SSH, host inspection, logs, ZFS, and safe file transfer. It exposes flux and scout MCP tools with parity from the original TypeScript server.

An MCP server that gives an LLM full control over a VMware-hosted Windows VM: lifecycle, snapshots, remote execution, file transfer, and kernel debugging.

Enables AI agents to dynamically spawn, route to, and manage ephemeral containerized sandboxes on Kubernetes without requiring Custom Resource Definitions or cluster-level operators.

MCP server that lets an AI agent manage Proxmox VE in natural language, with policy-driven security, read-only mode, two-step confirmations, and audit logging.

An MCP server designed to help AI models refactor Kubernetes configurations by analyzing Kustomize dependencies and rendering manifest diffs across environments. It provides tools for computing file dependencies, rendering overlays, and comparing configuration changes through a checkpointing system.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.

An MCP server that gives LLM agents full API access to a VMware Cloud Foundation 9.1 estate, exposing 8,931 operations through eight tools with automatic authentication, async task tracking, and write safety.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

VMware vSphere compliance and hardening — read-only baseline scanning plus drift detection across CIS, DISA STIG, vSphere SCG, China DJCP 2.0, and PCI-DSS frameworks. Includes LLM-powered remediation suggestions; apply-side gated through the vmware-pilot approval workflow.

A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.