A MCP server that collects interactive user feedback during AI-assisted development, reducing unnecessary tool calls and costs by enabling AI to confirm with users.
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.
Enables AI agents to render interactive user interfaces such as forms, dashboards, charts, tables, and wizards directly in MCP-compatible clients. Supports structured data collection and richer interactions beyond text responses.
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 bidirectional communication between AI coding assistants and Telegram, allowing interactive confirmations via inline buttons, media and screenshot ingestion, and on-demand message polling without a background daemon.
MCP server that gives AI agents real interactive terminal sessions for running REPLs, SSH, database clients, and any interactive CLI with clean text output and smart completion detection.
Enables AI agents to generate and package SCORM 1.2 compliant interactive learning activities (matching and quiz) with a 16:9 responsive player shell, including scoring, timers, lives, and synthesized audio.
MCP server for managing interactive processes, enabling AI agents to start, interact with, and terminate long-running programs like SSH sessions, REPLs, and installers via read/write operations.
Enables AI assistants to interact with Interactive Brokers trading accounts to retrieve market data, check positions, and place trades. Includes pre-configured IB Gateway and handles OAuth authentication automatically.
A powerful MCP server that provides interactive user feedback and command execution capabilities for AI-assisted development, featuring a graphical interface with text and image support.
Enables LLMs to create and manage persistent, interactive shell sessions with full terminal emulation and PTY support. It allows for sequential command execution and supports interactive programs like vim or htop through specialized streaming and snapshot output modes.
Enables AI agents to interact with interactive CLI processes via a real PTY, allowing them to send keystrokes, read screen output, and handle interactive prompts.
MCP server that enables AI agents to run fully interactive SSH sessions (via tmux) and execute commands like a human operator, with persistent sessions and multiple concurrent connections.
Enables AI assistants to request user input through interactive popups in VS Code, supporting button selections, text inputs, and confirmation dialogs. This system allows for seamless human-in-the-loop interactions without interrupting the conversational flow.
Provides AI agents with fully interactive terminal sessions, including TUI support, keyboard control, and screen capture across Windows, Linux, and Mac.
Provides production-ready examples of MCP servers that demonstrate building rich, interactive UI components for ChatGPT, including authentication flows, product search with carousels, shopping cart checkout, and membership signups with state management.
Provides stateful, interactive terminal access for LLMs to spawn and maintain persistent processes like SSH sessions, debuggers, and REPLs with continuous input/output interaction across commands.
Enables AI agents to prompt users for input directly within the chat UI using MCP's elicitation capabilities, allowing for interactive multi-turn conversations without leaving the conversation interface.
Enables users to draw GIS geometry on an interactive map and get clean, validated GeoJSON to hand off to other GIS MCP servers such as FEMA flood screening and USGS hydrography.
Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.
Interactive, streaming SSH tool for LLM agents that enables spawning long-running remote commands with live line-by-line output, signal handling, stdin input, and SFTP file transfer.
An MCP server that bridges VS Code Copilot to your mobile device, allowing you to monitor task progress and respond to decision prompts while away from your desk. It features real-time push notifications, a web-based dashboard, and interactive tools for remote code review and approval.
MCP server that lets agents create, display, and export rich UI widgets (cards, dashboards, charts, forms) inline in conversations, with interactive iframe support in MCP Apps hosts and PNG image fallback for other clients.
Enables analysis of JVM thread dumps to detect deadlocks, CPU spikes, pool exhaustion, and virtual thread pinning, returning a health score and interactive report link.
A demo MCP server that returns an interactive dashboard (bar chart with dataset selector) as an MCP App via the official MCP Apps extension (SEP-1865).
Enables AI assistants to plan container and truck loads from plain-English shipment descriptions, returning fitted containers, utilization, non-fitting items, and interactive 3D load plans.
An MCP server for the iNavi Maps API that gives AI assistants iNavi Maps API specifications and ready-to-use HTML
templates for interactive map visualizations (geocoding, POI search, route planning).
Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.
Self-hostable remote terminal assistance over MCP. Agents create one-command connection invitations, execute commands, and manage interactive sessions on user-authorized macOS, Linux, and Windows computers without requiring an SSH daemon.
Enables AI agents to build, validate, preview, and read content-only H5P packages locally for interactive content types such as multiple choice, fill in the blanks, cards, question sets, and course presentations.
A Model Context Protocol implementation that plays sound effects (completion, error, notification) for Cursor AI and other MCP-compatible environments, providing audio feedback for a more interactive coding experience.
Interactive feedback layer that lets users pin comments on live web apps with auto-captured context (failing requests, console, AI metadata), and coding agents fix issues via MCP, turning pins green upon verification.