A secure terminal execution server that enables controlled command execution with security features and resource limits via the Model Context Protocol (MCP).
A MCP server that enables human-in-the-loop workflow in AI-assisted development tools by allowing users to run commands, view their output, and provide textual feedback directly to the AI assistant.
An MCP server that enables LLMs to ask users questions through a web interface with keyboard shortcuts, supporting single/multiple choice and custom input.
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.
Complete Model Context Protocol (MCP) server designed to facilitate seamless interaction between Large Language Models (LLMs) and end-users. It provides a robust set of tools for notifications, confirmations, selections, and text inputs, supporting multiple rendering modes including Console, GUI, and Telegram Bot.
An MCP server that lets LLM agents dispatch native OS notifications when a task finishes. It supports cross-platform desktop notifications, task tokens for updates, mobile bridges, and quiet hours.
A cross-platform MCP server that provides native popup windows for AI agents to gather user feedback, input, and safety confirmations. It enables agents to present interactive questionnaires and secure confirmation prompts for sensitive operations like file deletion or code execution.
A lightweight MCP server that enables AI assistants to collect interactive user feedback via a browser window with full Markdown rendering and syntax highlighting.