"A resource for designing user interfaces" matching MCP servers:

Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

An MCP Server that provides a natural language interface to Google Cloud Resource Settings API, enabling users to view and manage settings for Google Cloud resources through conversation.

An MCP server that connects to the Resource Hub, allowing centralized configuration and management of tools and resources across different MCP environments.

Estimates physical quantum resources (qubit count, runtime) for quantum algorithms on fault-tolerant hardware through natural language queries.

Exposes user, membership, and role administration tools via MCP, acting as a thin passthrough to a coordinator API with RBAC enforced by the coordinator using caller bearer tokens.

Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.

Minimal MCP server for testing client support for resources/subscribe and notifications/resources/updated, simulating an asynchronous status update.

It enables AI agents to parse user agent strings into structured data such as browser, OS, device type, engine, and bot status, with pay-per-call micropayments via x402 and no API key or signup required.

MCP server that enables Claude to pause and ask clarifying questions via Emacs.

Lets Claude Code conduct long, structured interviews via a keyboard-driven local web form, with unlimited questions and options, recommendations, ranking, previews, and live follow-up questions.

Enables Codex to clarify requirements via native MCP elicitation controls, supporting single/multiple-choice and free-text questions with recommended answers and a discuss-first option.

Enables AI models to ask users questions through a local web interface, supporting batch questions, multi-select, and free text for human-in-the-loop interactions.

Provides an interactive checklist tool that allows AI agents to present step-by-step instructions to users through an automatically opened terminal UI. It enables agents to guide users through manual tasks and wait for completion, skipping, or feedback before proceeding.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A server that lets AI agents ask users clarifying questions mid-task via a pop-up terminal window, enabling interactive context gathering.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

An MCP server providing tools for user information management with capabilities for retrieving, searching, and adding user data stored in a JSON file.