"A tool for generating UI design mockups from text descriptions" matching MCP servers:

Ply — ply-ui.com — is an Angular + Tailwind copy-in catalog for coding agents. List, search, and inspect 218 components (128 MIT). This host is read-only and returns npx ply-ui-cli add . Local stdio: npx -y ply-ui-mcp. Not MUI Base UI.

Enables AI-driven generation of UI components, full applications, and backend code across multiple frameworks (React, Vue, Angular, Svelte, HTML) with Figma integration and brand identity support.

MCP server that renders bar, line, and pie charts from data using QuickChart, returning PNG file paths.

Enables AI coding agents to plan, build, and review websites and product interfaces with a persistent, user-led process, including design direction, component contracts, and implementation review.

Provides AI assistants with comprehensive access to Grafana's React component library, including TypeScript source code, MDX documentation, Storybook examples, test files, and design system tokens for building Grafana-compatible interfaces.

Provides AI assistants with comprehensive access to Taiga UI components, enabling retrieval of component documentation, code examples, and migration guides via four MCP tools.

AI Design Blueprint is a doctrine and runtime standard for agentic AI: 10 principles, 16 laws, and Pro/Teams validators your coding agent calls over MCP.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

A standalone Model Context Protocol service that connects MasterGo design tools with AI models, enabling AI models to directly retrieve DSL data from MasterGo design files.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

Manage a fleet of OPNsense firewalls from an AI agent, inside guardrails it can't drive around. MCP server for central management of OPNsense firewall fleets. 129 tools across devices, config sync, tasks, schedules, templates, backups and remote consoles - destructive actions confirmation-gated, MCP-issued tokens lifetime-bounded, backup and storage secrets excluded from the toolset entirely.

Answers why a specific number in a Chinese listed company moved — margins, cash flow, inventory, management commentary, policy impact — by reading filed reports and IR transcripts and returning figures with the document and announcement number attached. It deliberately refuses price, valuation, and recommendation queries, returning a "gone_by_design" error instead.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

Provides AI assistants with access to WordPress Design System component information and design guidance.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Lets an AI assistant read call and message history, send texts and picture messages, reach Phone Book contacts by name, and — once switched on — place calls run by a voice agent, all limited to the phone numbers the user ticks. Hosted remotely with OAuth sign-in, so nothing needs to be installed locally.

Connects AI models to MasterGo design tools, enabling retrieval of DSL data, component documentation, and metadata from MasterGo design files for structured component development workflows.

Enables autonomous agents to automatically repair and guard tool-call schemas through deterministic AST analysis and parameter projection validation, ensuring reliable, schema-compliant interactions in MCP-compatible environments.

Enables agents and MCP-compliant clients to resolve tool execution graphs by scheduling calls as a topological dependency DAG, running independent tools in parallel batches while speculatively prefetching and evaluating arguments. This cuts latency and token burn by handling routine tool orchestration deterministically without extra LLM round-trips.