"Project Management for Aircraft Development" matching MCP servers:

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 VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

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,

A Node.js application that provides a JSON-RPC interface to interact with CO2 sensor data, working in both simulation mode and with real Raspberry Pi Pico hardware connections.

Enables AI assistants to automate DDEV development environments, including project management, database operations, and executing commands for various CMS frameworks.

Enables AI assistants to interact with DDEV local development environments by querying databases, managing project states, and executing container commands. It provides comprehensive control over local services with a security-first approach using whitelisted operations.

MCP server that integrates with Coolify to let AI assistants manage Coolify instances via a clean toolkit wrapping the official REST API.

Enables AI-powered creation, configuration, and management of DevContainer environments using natural language prompts. Supports 11+ templates for popular development stacks and provides container lifecycle operations through VS Code, Cursor, or any MCP-compatible editor.

Enables AI assistants to control Unreal Engine via Remote Control API for game development automation, including asset management, actor control, level editing, animation, physics, visual effects, and cinematics creation through natural language.

HTTP MCP adapter for requesting VMs and inspecting state. Part of the vm-forgeyard KVM control plane for test and development virtual machines.

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.

AI-powered cloud development IDE, so you can run AI to surf in a secure sandbox environment.

Enables management of KVM/QEMU virtual machines on remote libvirt hosts via SSH, with tools for inspection, lifecycle management, snapshots, and cloning.

MCP server for generating and configuring development containers from devcontainer.json files, enabling management of devcontainer environments through tools like devcontainer_up, devcontainer_exec, and cleanup.

Exposes the Dockhand Docker management API as tools for LLMs, enabling container, stack, image, volume, and network management via natural language.

This MCP provides comprehensive tools and resources for MSX software development, testing, and automation through openMSX emulator.

Enables secure execution of shell commands and file operations within isolated Docker containers. Provides process management, interactive input handling, and comprehensive file system operations for containerized development environments.

Provides MCP multi-cluster Kubernetes management and operations. It can be integrated as an SDK into your own project and includes nearly 50 built-in tools covering common DevOps and development scenarios. Supports both standard and CRD resources.

MCP server for IBM Z Hardware Management Console Web Services API integration with Bob AI, enabling management of HMC systems and partitions through natural language.

A middleware service that allows LLMs and AI assistants to directly interact with the Dokploy platform through a standardized interface, providing access to Docker, project, and application management capabilities.

Provisions Docker-based development environments on demand, allowing AI agents to create, manage, and inspect containerized dev environments without manual setup.

Provides isolated Docker environments for code execution, enabling users to create and manage containers, execute multi-language code, save and reproduce development environments, ensuring security and isolation.

Free MCP server for easy deployment and management of MCP tools via Docker, tailored for the Xiaozhi community.

Enables comprehensive Ansible automation management through natural language, including playbook creation and execution, inventory management, role scaffolding, and project workflows. Supports both local inventories and full project lifecycle management with syntax validation and idempotency testing.

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.

Lets Claude manage a Docker homelab through Arcane by wrapping the pinned arcane-cli with policy-checked tools for running commands, reading logs, inspecting environments, and editing or creating compose projects with built-in confirmations and secret redaction. It also serves operational playbooks and live Arcane documentation so updates, cleanup, and CVE triage follow safe, guided workflows.

Enables AI agents to inspect pending updates and service health for Proxmox VE VMs and containers, then take snapshots, apply official updates, reboot, and roll back under tag-based permissions and human-confirmed risky actions.

GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC

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.

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

MCP server for managing Proxmox VE resources, VM/CT lifecycle, snapshots, backups, and clones via natural language.

Enables unified administrative control over Cloudflare, Porkbun, Docker, Proxmox VE, Nginx Proxy Manager/NPMPlus, Uptime Kuma, Authentik, and Coolify. Exposes service discovery and action execution through three MCP tools with roughly 150 cataloged operations for managing DNS, containers, VMs, proxies, monitors, users, and related infrastructure.

Connects Claude Desktop to any Kubernetes cluster, enabling natural language queries for diagnostics and operations such as listing pods, viewing logs, scaling deployments, and more.

A self-hosted MCP server providing a governed interface for AI agents to interact with local Docker infrastructure, featuring a two-phase confirm protocol for state-changing operations and append-only audit logging.

MCP server for Proxmox VE and Proxmox Datacenter Manager, covering every API endpoint via six consolidated tools for list, describe, and call operations with a read-only safety gate.

Enables AI-assisted management of vCenter Server and standalone ESXi hosts, including lifecycle, deployment, guest operations, cluster management, datastore browsing, alarms, and investigations through natural language.

A read-only MCP server for Proxmox VE that provides AI assistants with structured visibility into cluster nodes, guests, storage, and Docker workloads. It is designed to prevent any mutating operations by construction.

MCP server for controlling PNETLab v6 network labs via natural language, enabling topology creation, node management, config push, console interaction, and link fault injection.

Enables AI agents to interact with Kubernetes clusters through progressive disclosure, where agents discover TypeScript modules via filesystem, write and execute code, and receive summarized console output for cluster management tasks.