"Connecting a Browser" 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.

Provides direct, unsandboxed local machine access via filesystem, Python, Node.js, and shell commands for MCP agents.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

Enables natural language SSH server management via Claude Code, allowing users to read logs, check services, run commands, and transfer files across multiple servers.

Enables a private ChatGPT app to remotely control a Windows PC through file operations, PowerShell, screenshots, mouse and keyboard input, clipboard, and Chrome browser automation.

MCP server that provides AI access to a local terminal, enabling command execution, directory navigation, and system operations with persistent session state.

A comprehensive MCP server that enables AI models to perform local file operations, command execution, and task management across multiple platforms. It features advanced capabilities like row-level file editing, directory searching, and system monitoring with built-in security filters.

SSH Session MCP fills a gap in the MCP ecosystem by offering a persistent shared SSH PTY runtime, not just stateless command execution. It features browser collaboration, input locking, safe/full execution modes, async command tracking, configurable policy rules, and multi-device profiles. Ideal for remote development, embedded systems, infrastructure workflows, and hardware control scenarios.

Self-hosted MCP server that gives AI assistants a real Linux development environment: file editing, shell commands, tmux terminals, and browser screenshots, with bounded access through a project registry and write gates.

Enables any MCP-compatible AI, whether in the browser or running locally, to create and edit projects, run terminal commands and long-running jobs, and optionally use Docker, all guarded by a policy engine, workspace jail, authentication, and audit logging.

Enables AI assistants to autonomously investigate and manage Sophos Channel Server incidents by connecting via SSH, checking Zabbix alerts, searching Jira, pattern matching known root causes, and creating LINFRA tickets.

Maps shell commands to standard MCP tools using single-file YAML specs.

Terminal\[X]MCP is a Model Context Provider (MCP) server that enables intelligent terminal automation through a multi-agent system with distributed specialized roles for command execution, security validation, and real-time monitoring.

Enables SSH operations including connecting to remote servers, executing commands, and transferring files between local and remote systems. Supports multiple SSH connections with both password and private key authentication methods.

A simple MCP server that provides waiting functionality to pause until other tasks finish, with progress reporting and support for CLI or HTTP server with SSE.

Enables AI models to access and manage SSH connections through a standardized interface, allowing AI assistants to perform SSH operations like connecting to servers, executing commands, and managing files.

Provides comprehensive Windows system control including file operations, process management, window control, screenshots, clipboard access, PowerShell/CMD execution, and optional mouse/keyboard automation and browser control capabilities.

A Codex-style MCP server providing 126 tools to operate a Kali Linux machine from ChatGPT or any compatible MCP client, including shell execution, filesystem operations, Git, Docker, browser automation, and security tool wrappers.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

Gives AI agents shell access by providing a run_command tool for executing shell commands and returning stdout, stderr, and exit code.