"Information about 'Terminal'" matching MCP servers:

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.

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.

Give AI agents a persistent, interactive terminal with support for SSH, REPLs, database CLIs, TUI apps, and long-running processes.

Enables AI assistants to execute terminal commands on a host machine with configurable, granular permission controls and safety protections. It features multiple security modes, including allowlists and manual approval, to ensure safe command execution within specified directories.

Enables AI agents to interact with terminal-based TUI applications by capturing visual terminal output as PNG screenshots and simulating keyboard input through a virtual X11 display.

Lets AI hosts answer questions about Kenda token spend and waste directly from the terminal.

Enables users to retrieve and structure shipment tracking information from DB Schenker's website using natural language queries.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

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

Windows-focused MCP server for terminal automation with persistent PowerShell sessions, live session logs, and VS Code integrated terminal bridge.

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.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Agent-native SSH control plane with a local Web Terminal, human-in-the-loop secret input, keychain-backed profiles, and user-confirmed uploads for Codex, Claude Code, and MCP-compatible coding agents.

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.

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

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.