"GNOME Terminal" matching MCP servers:

GNOME desktop automation for AI agents. 30 tools via D-Bus: screenshots, window management, mouse/keyboard injection, clipboard, workspaces, and system notifications. Works on any GNOME 45–49 Linux desktop.

Enables AI agents to start and stop native GNOME Shell screen recordings via MCP tools, returning JSON with file path, size, and duration without depending on ffmpeg or wf-recorder.

Enables management of visible, interactive terminal sessions across platforms (macOS, Windows, Linux, WSL). Supports creating, executing commands, capturing output, and managing multiple terminal windows simultaneously.

Security-hardened MCP server that runs only allowlisted commands with no shell, jailed to a single directory, and bounded execution.

An MCP server that lets an AI agent use a real terminal the way a person does: type, press keys, click, read the screen, take a screenshot.

Enables AI agents to drive genuine interactive Windows console sessions through ConPTY, so they can launch PowerShell, pwsh or CMD, send keystrokes, answer prompts, watch rendered screens and block until output matches. Multiple persistent shells can run in parallel, supporting live input, incremental reads, interrupts and window resizing.

Enables AI models to run interactive tmux terminal sessions that a human can watch and type into, with all output logged and split into searchable per-command regions so only needed lines enter context. Also guides models through unfamiliar tools by returning exit statuses and key output alongside advice on the tool being used.

Enables MCP clients to start and control Owner-approved local POSIX subprocess sessions over stdio, with cursor-based output reads, input writes, status checks, termination, and resource/time limits.

Enables secure terminal command execution, directory navigation, and file system operations through a standardized interface.

An MCP server that enables secure terminal command execution, directory navigation, and file system operations through a standardized interface for LLMs.

Lets ChatGPT, Claude Desktop, Claude Code, and other MCP clients run an allowlisted set of local commands and read files from a chosen directory, so an assistant can analyse a codebase or trigger local generators (images, sprites, assets) without metered API tokens. The server is read-only and deny-by-default by default, with no shell, path containment, opt-in writes, and required auth when exposed over HTTP.

Enables an agent to see and operate a GNOME Wayland desktop like a human, including screenshots, mouse/keyboard control, accessibility tree access, OCR, clipboard, and audio listening.

An MCP server for creating and managing shared terminal progress bars from AI agents, enabling real-time tracking of parallel tasks.

Enables AI agents to open persistent interactive terminal sessions with network devices over SSH, Telnet, TCP console, or serial, write raw commands including nested ssh/telnet transitions, and read full output without requiring a particular prompt format. It supports multiple concurrent sessions and keeps credentials/secrets out of MCP arguments or audit logs.

Enables AI agents to create and control persistent terminal sessions, run and monitor asynchronous jobs, page through ordered event history, and resolve registered device connection details without exposing stored secrets. Exposes 15 MCP tools over stdio that mirror a REST API, keeping session state alive independently of the agent that started it.

An MCP server that enables users to execute arbitrary shell commands on their local machine and receive the output. It provides a terminal tool for running system commands through MCP-compatible clients using the Python SDK.

Enables AI agents to execute and interact with terminal commands through MCP, supporting command-line operations and workflows.

Enables AI agents to run shell commands, execute Python code, read and write files, search text, and create or delete folders through MCP stdio tools.

A lightweight MCP server that enables AI assistants to interact with the local machine through terminal, filesystem, and Python execution tools.

Enables MCP clients to observe and, when explicitly enabled, send constrained input to whitelisted tmux sessions, with support for local STDIO and loopback-only HTTP transport behind an authenticated tunnel.