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 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 interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.
An MCP server that enables human-in-the-loop elicitation, letting AI agents ask users questions via tools like elicit_confirm and elicit_form, with diagnostics to verify host elicitation support.
An MCP App that enables AI agents to ask users multiple questions with tab-based navigation, multiple-choice options, multi-select support, and custom text input, all rendered inline in the conversation.
