"Guidance on interacting with the Things application" matching MCP servers:

A read-only MCP server that provides visibility into Parallels Remote Application Server infrastructure, policies, and sessions through the RAS REST API. It enables AI assistants to query site settings, published applications, and license status without performing any modifications.

A Model Context Protocol (MCP) server that interfaces with the Apache YuniKorn Scheduler, allowing AI agents to observe and reason about Kubernetes batch workload resource management, queue hierarchies, and application states.

Enables AI agents to control the Android Emulator through adb, including booting AVDs, installing and managing apps, interacting with the UI, taking screenshots, reading logs, and more.

Serves as a personal MCP hub for development, detecting the current stack and monorepo root, managing Docker Compose actions, querying Context7 documentation, and interacting with Nexus, while also forwarding tools from optional external MCP servers.

Enables AI agents to manage server infrastructure through the 1Panel API, including Docker containers, databases, and system monitoring. It provides tools for website management, file operations, and application deployment via natural language commands.

MCP server for managing Pterodactyl game panel resources (users, servers, nodes, locations, etc.) via the Application API.

Enables managing Pterodactyl Game Panel servers via Client and Application APIs, including power actions, files, databases, backups, schedules, and administrative operations.

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

MCP server for interacting with QUADS infrastructure systems via API, enabling resource management and automation through LLM applications.

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

An MCP server for interacting with Azure. Contains some common Compute and Networking actions, and extensible to add many more.

Enables server operations and AI application deployment via 16 MCP tools, including container management, disk diagnostics, and GitHub repository search with one-click deployment, through natural language.

Enables LLMs to dynamically orchestrate containerized application deployments to a Kubernetes cluster, handling configuration validation, manifest generation, dry-run planning, and service endpoint extraction.

An MCP server for interacting with the Proxmox Virtual Environment API, enabling management of VMs, containers, storage, and cluster resources 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.

Provides tools for interacting with Azure services including Storage, Virtual Machines, and App Service operations.

Enables running arbitrary JavaScript code in isolated Docker containers with on-the-fly npm dependency installation, supporting both ephemeral one-shot executions and persistent sandbox environments.

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.

An MCP server that gives any LLM client the ability to list, inspect, start, stop, and monitor Docker containers on the host machine.

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.