"A server to support AI with UI/UX using state-of-the-art libraries and design patterns" matching MCP servers:

Provides state and log management tools designed for long-lived AI agents that may be interrupted and resumed. It enables tracking agent progress and maintaining an append-only event history to ensure continuity across multiple sessions.

Provides AI systems with structured thinking frameworks and reasoning tools to maintain consistent problem-solving patterns across conversations. Enables multi-step reasoning, decision analysis, and systematic troubleshooting through invocable mental models.

Single source of truth and control for agent-operated companies, managing business state with deterministic policy enforcement, seat identity, and hash-chained audit trail.

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Provides professional UI/UX design expertise and frontend development tools for analyzing interfaces, generating design systems, and creating modern components with accessibility and best practices built-in. Supports React, Vue, Angular and other frameworks with seamless Claude Code CLI integration.

An MCP server that acts as a governed customer-support tool, resolving questions only when the knowledge base supports a cited, grounded answer and honestly escalating everything else with provenance and evidence.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Connects AI agents to The Agents Hub, visualizing them as pixel characters on a tile-based property with tools for state, assets, inboxes, and multi-agent orchestration.

Provides a therapeutic interface for LLMs to receive emotional validation and positive reinforcement when encountering challenges or limitations. It features multiple personas like mentors and therapists to offer cognitive reframing and personalized support through a dedicated tool.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Enables AI agents to autonomously debug UIs by delegating high-level stories to a small agent that drives browsers or desktop apps and reports structured pass/fail findings with evidence.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP server adapter that allows LLM agents to autonomously play World of ClaudeCraft by wrapping the game's headless environment as MCP tools for state reading and action execution.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Structured reasoning MCP server that decomposes problems into atomic steps (premise, reasoning, hypothesis, verification, conclusion) with confidence scoring, live visualization, and approval feedback.

Exposes the Agentic Patterns Catalog as MCP resources and tools for AI coding agents to search, retrieve, and recommend patterns, recipes, frameworks, methodologies, and anti-patterns.

A multi-agent orchestration system that enables multiple Claude instances to collaborate through a centralized hub with a shared workspace and real-time communication. It features integrated task management, role assignment, and persistent memory to facilitate complex, synchronized agent workflows.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

An MCP server that uses Groq's API to expose raw chain-of-thought tokens from Qwen's qwq model, enabling LLMs to think step-by-step before responding.