"Designing UI (User Interfaces)" matching MCP servers:

MCP server that synthesizes user feedback from multiple sources into actionable insights. Aggregates reviews, support tickets, and survey responses to identify patterns and priorities.

MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.

Enables AI coding agents to inspect user feedback on live web apps, read full reports and recording timelines, update status, and reply in threads so fixes can be checked and confirmed by reporters.

Turns product feedback pinned to a live UI into an actionable backlog for Claude Code — list comments, open one with its target element's HTML, computed styles and screenshot, and update its status.

Enables AI assistants to create interactive prototypes, annotate UI elements, generate PRDs, and track which annotations and documents need updating after changes.

Creates synthetic user profiles from research data to validate service designs through natural conversation.

Enables reading release lifecycle status, recent written reviews and bulk monthly report CSVs for allowlisted apps, and searching the full pinned Play API catalog with each method's implementation status. Read-only by design, with keyless authentication, explicit app allowlists and bounded, GET-only access to official Google interfaces.

MCP server for reading public Featurebase feedback boards, enabling agents to query user feedback, posts, comments, and statistics.

MCP server for product analytics using dot plots to visualize individual user activity, with tools for user classification, aha moment detection, retention analysis, and generating shareable HTML reports.

Captures and organizes requirements as markdown, tracks relationships between personas, requirements, use cases, and user stories.

An AI-powered Product Management Operating System that provides tools for PRDs, user stories, prioritization, competitor analysis, roadmaps, KPIs, meeting notes, and product strategy via MCP clients.

Enables management of Azure DevOps work items including Epics, Features, User Stories, Tasks, and Bugs through natural language. Supports CRUD operations, WIQL queries, work item relationships, and retrieval of project metadata such as iterations and area paths.

Run real user interviews from AI agents and retrieve structured insights with themes and verbatim quotes.

TruePPM MCP servers ask real questions of your self-hosted TruePPM instance: the critical path, a Monte Carlo slip forecast, sprint status, the risk register, My Work. Answers are computed server-side by the same CPM/Monte Carlo engine the web UI uses, never guessed by a model, and nothing leaves your box.

Enables reading and editing Avo tracking plans through natural language, with skills for designing new plans and working with existing ones.

Remote MCP server for Pruva, enabling AI assistants to manage products, features, and documents over HTTPS with OAuth authentication.

Enables AI agents to research mobile apps, compare onboarding and paywall flows, explore App Store reviews, and find visual UI references, bringing real screens and market context into their research.

Collect and analyze user feedback from any app via a single API endpoint, with MCP tools for listing, searching, and stats.

Connects AI agents to the Outset research platform for creating studies, managing recruitment, and querying results via the Model Context Protocol.

Provides an MCP Apps interface to the Upvote Club API, enabling task management with an inline progress card UI in Claude.