"Tools for Testing in Python and Java" matching MCP servers:

Provides Docker management tools for AI agents, including inspecting containers, images, Dockerfiles, and Compose configurations.

Enables AI assistants to manage OpenStack cloud resources including compute, images, identity, network, and block storage via the Model Context Protocol.

Enables coding agents to list and boot iOS Simulators and Android Emulators, capture screenshots, drive device interactions through accessibility snapshots, and end sessions.

Provides read-only, governance-audited operations for OLVM and oVirt 4.5 engines, enabling inventory, health, capacity, and diagnosis queries over MCP and CLI with audit logging and budget guards.

AI-powered MCP server for managing Proxmox VE VMs and containers with built-in governance, audit logging, and reversibility.

An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.

Enables AI assistants to manage Coolify infrastructure including servers, applications, databases, deployments, and 80+ one-click services through 98 comprehensive tools for both cloud and self-hosted instances.

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.

Governed XCP-ng operations via Xen Orchestra REST — VM-health, SR-usage, backup-failure, and patch-state RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

AI-powered Veeam Backup & Replication operations MCP server with tools for managing jobs, restores, sessions, and repositories, featuring built-in governance, audit logging, and safety controls.

Governed Kubernetes operations for AI agents with 15 MCP tools, audit logging, policy engine, and safety features.

Governed AI-ops MCP server for Nutanix Prism Central v4 REST API, offering 47 read/write tools for clusters, VMs, storage, network, catalog, data protection, alerts, and LCM upgrades with built-in audit, budget, and risk-tier governance.

Governed Docker + Portainer container-host operations (non-Kubernetes) — restart-loop, resource-pressure, and image/volume-bloat RCA, with guarded lifecycle writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

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.

MCP server for Cisco Modeling Labs (CML) that enables building, managing, and running network labs through MCP tools, wrapping the CML Python SDK for lab/topology CRUD, node/link management, and configuration.

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

A server implementation that enables remote Python code execution in Unreal Engine environments, featuring automatic Unreal node discovery and management through a multicast network.

Enables AI-powered management of Ludus cyber range environments through natural language commands. Provides 157 tools for range lifecycle management, scenario deployment, template creation, Ansible role management, and SIEM integration for security testing and research.

An MCP server that enables agents to attach debugpy to running Python processes inside Docker containers for enhanced debugging and inspection. It provides tools for container autodiscovery, process injection, and generating breakpoint plans based on logs and metadata.

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,

Enables AI agents to spin up real Linux desktops in Docker and drive them by reading windows, pages, and documents as text and acting with tools like opening apps, running menu commands, filling file dialogs, and exporting files. It exposes these capabilities uniformly over MCP, function calling, HTTP, CLI, and Python/TypeScript SDKs, with token-efficient diffs, code mode, and parallel or forked desktops.

A Python-based server enabling interaction with Proxmox hypervisors. It supports secure authentication and provides tools for managing nodes, VMs, clusters, and storage.

A Python-based MCP server for interacting with Proxmox hypervisors, enabling management of nodes, VMs, containers, and executing commands via QEMU Guest Agent.

Lets AI agents inspect Kubernetes clusters in plain English, exposing read-only tools for pods, deployments, services, events, and logs, with mock and real backend support.

An enhanced Python-based MCP server that enables complete VM lifecycle management and monitoring of Proxmox virtualization platforms through natural language, with 11 REST API endpoints for seamless integration.

A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.

Enables users and LLMs to execute Python code, install packages, run terminal commands, and upload files in isolated Docker containers, returning outputs and HTTP links to generated files through an SSE interface.

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

Enables network configuration, connectivity testing, and routing management for ContainerLab Linux containers through an MCP interface.

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.

A demonstration MCP server that simulates server management actions for Contabo and Hetzner using FastAPI. It provides a mock environment for testing request routing and provider-based service modules without requiring live API credentials.

Provides MCP tools for managing disposable Docker sandboxes that let AI agents safely execute commands in isolated, ephemeral environments.

Enables safe Python code execution in isolated Docker containers through the AgentRun framework. Provides automatic container lifecycle management and comprehensive error handling for secure and reproducible code execution.

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 an AI agent to view and control VMware vSphere VM consoles—screen, mouse, and keyboard—through vCenter, without installing anything in the guest.

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

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.

Install and manage a self-hosted XNS Relayer — S3-compatible distributed object storage — conversationally over stdio. 15 tools cover prerequisites, account registration, install, claim, health, VPD configuration, S3 verification, CLI credentials, settings, restart, and backups.

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.