"Browser Application" matching MCP servers:

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.

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

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.

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 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.

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.

Provides AI agents with isolated virtual desktops containing a real Chromium browser, enabling them to see, click, type, and navigate like a human, with features like snapshots and remote control.

Enables AI agents to create isolated Docker runtimes, execute commands, manage workspace files, drive a headed browser, and retrieve artifacts through eight semantic MCP tools, with progressive capability discovery and explicit sandbox lifecycle.

Enables AI agents to operate a real, private, local Docker-based computer with durable files, terminal access, web research, and a persistent browser or desktop. It supports multiple agent clients via MCP or OpenAPI, with live viewing and human takeover.

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 remotely control VirtualBox VMs and Playwright browsers on Windows, including VM lifecycle actions, in-guest commands, browser automation, window management, and service monitoring via REST API and MCP.

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.

Enables AI agents to fully control an Android emulator via MCP, including UI interaction, screenshots, APK installation, logging, and clipboard access, with optional live browser viewing for humans.