"Iterating on UI designs and improving prompts" matching MCP servers:

Search, inspect and install the 21 free MIT components of Marvelous UI (framework-agnostic Web Components and CSS) and their design tokens into a project. Runs locally over stdio with no network calls.

A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.

Provides Claude with persistent memory and learning capabilities through 10 automatic agents that capture decisions, errors, solutions, and patterns across conversations. Features an anti-compaction system to prevent context loss and enables infinite conversation continuity.

Lightweight MCP server for providing user prompts defined in Markdown with argument support.

A simple MCP server for utilizing prompts defined in YAML files.

MCP server that lets AI agents search and inspect shadcn components from the encode-ui registry, returning metadata, source code, and install commands.

Bidirectional MCP bridge enabling AI assistants to draw UI on Figma canvas and read designs back as structured data or code tokens via localhost, requiring Figma Desktop.

Enables MCP clients to read design structure, take screenshots, create nodes, and edit UI directly on Figma canvas via a bridge between MCP and Figma Desktop.

MCP server for the coss ui design system, enabling AI agents to fetch components, props, and design tokens on demand for accurate, low-cost code generation.

Enables coding agents to see the UI they just changed without flooding their context window, returning a structured text summary (console errors, failed requests, overflow, layout shifts, accessibility violations) plus small crops of only the regions that changed since the last capture. All output is fitted into a chosen token budget, with captures stored on disk and evicted automatically.

Enables offline composition and validation of Basecoat UI interfaces in Astro and static HTML projects via curated templates, design resources, and static checks.

Enables UI debugging on physical iOS devices by bridging to an in-app DebugBridge HTTP service, supporting UI inspection, element interaction, log retrieval, and runtime validation.

Enables AI-driven UI inspection and optimization by scanning websites with configurable viewports, capturing screenshots, running deterministic accessibility and layout checks, and generating prioritized reports with fix prompts.

A TypeScript server that enhances AI assistants' capabilities when working with Starwind UI components, providing tools for project initialization, component installation, documentation access, and more.

Enables AI models to generate interactive visuals including charts, diagrams, UI mockups, and SVG graphics from plain text prompts. This Windows-based MCP server serves as an intermediary to bridge AI tools with visual output capabilities.

Imports public websites and extracts UI components and design tokens, making them available via MCP for AI coding agents to reuse in implementations.

MCP server for managing AI prompts with CRUD operations, categorization, and tagging. Enables users to store, organize, and retrieve their favorite prompts efficiently.

A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.

A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.