"A guide to creating a presentation" matching MCP servers:

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

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 AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

A Node.js/TypeScript MCP server that facilitates interactive communication between LLMs and users, allowing AI assistants to request user input, display notifications, and manage command-line chat sessions.

A minimal MCP server that exposes a single bash tool to execute commands inside a devcontainer, returning real output and exit codes.

Enables AI assistants to manage local tmux sessions, including creating and controlling sessions, windows, and panes, sending commands, and capturing terminal output.

Enables users to manage short links via cliqo.link, including creating, listing, viewing, and revoking links, as well as checking credit balances.

Enables an MCP client to observe and control a text-mode DOS system via a Python bridge, supporting keyboard input and screen capture.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.

A Model Context Protocol (MCP) server for Gobuster that enables AI assistants to perform directory/file, DNS, virtual host, S3 bucket, and TFTP enumeration on a remote Kali Linux host via SSH.

A secure Model Context Protocol server that provides controlled filesystem access within predefined directories, enabling AI models to perform file and directory operations with strict path validation.

Enables programmatic control over tmux terminal sessions for SSH access, command execution, and terminal automation. Supports creating sessions, sending commands, capturing output, and managing multiple panes for interactive debugging and monitoring.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

Enables interaction with Railway cloud platform through the CLI to manage projects, services, deployments, and environments. Supports creating projects, deploying templates, managing environment variables, and monitoring logs through natural language commands.