"User interface design or related topics" matching MCP servers:

Enables Claude to search and retrieve curated design references, browse categories and tags, read style guides, and save new UI references from URLs so UI work starts from chosen inspirations rather than generic defaults.

An MCP server that enables AI agents to semantically retrieve premium UI components from Awwwards and adapt them into clean React + Tailwind code.

A local-first FastMCP server that indexes offline frontend catalogs (components, patterns, motion libraries) and exposes discover, search, compare, and recommend tools to AI agents via stdio.

Enables AI-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

Enables MCP-capable agents to retrieve relevant slices of a user-story knowledge graph (stored in Supabase + pgvector) using three retrieval verbs: find_related, find_crossover, and query_stories.

A read-only MCP server that enables semantic search over a Chroma library of narrative and game design content, using multilingual embeddings (BAAI/bge-m3) and offering tools to query indexed books, retrieve page chunks, and list available titles.

Multi-model adversarial design review MCP server that distributes design documents to multiple LLMs, retrieves project knowledge, and produces calibrated consensus summaries.

Perplexity AI search, reasoning, research, and compute - MCP server, dashboard, and multi-IDE auto-config for VS Code.

Provides semantic search and complete document retrieval by ID through OpenAI's Vector Store API, letting deep research agents access company-specific knowledge and tools.

MCP server for indexing, semantic search, and generation of multi-format documents. Exposes 13 tools over JSON-RPC 2.0 so an LLM can search your local PDF, Excel, and Word files, and create or edit Excel and Word documents.

Enables enterprise SaaS support teams to get retrieval-augmented answers from indexed support documentation and to run natural-language questions as SQL queries against a support PostgreSQL database. It returns answers with source references and exposes the generated SQL alongside its results, with optional tracing and evaluation.

Gives your AI persistent memory across conversations. Stores facts automatically, finds them by meaning using hybrid search with query expansion, and organizes everything into topics without manual tagging.

A server that provides AI agents with full OpenClaw documentation via BM25 search, enabling them to look up configurations, providers, and other topics without web lookups.

Search 1,500+ pre-verified, cited knowledge units across 16 domains. 6 tools: query, batch query, get unit, list domains, suggest topics, report issues. Free, no API key required.

Enables AI agents to persist facts with tags, sources, and importance in a local SQLite database, retrieve them through hybrid BM25 plus embedding search weighted by retention decay, link or supersede related entries, and review everything in a read-only visual dashboard showing the memory graph and timeline.

Enables AI assistants to create council hearings where multiple LLMs (Claude, GPT, Gemini, Grok) debate topics and synthesize verdicts with trust scores and diverse perspectives.

An AI-powered documentation navigator that enables intelligent search, summarization, and exploration of SUSE, Rancher, and related open-source documentation using local or cloud AI models.

MCP server that gives AI assistants direct access to live AVEVA PI System documentation, eliminating hallucination on PI-specific topics by fetching real answers from the official docs.

Enables searching and retrieving content from Grokipedia, with tools for page lookup, citations, sections, and related pages.

Enables AI agents to access a local-first personal context and memory layer through MCP tools for bootstrapping user context, semantically searching Markdown vault knowledge, reading files, listing topics, and adding controlled memories. It provides deterministic context retrieval, provenance-cited vector search, and secure vault operations while keeping data local and model-independent.

Enables AI agents to query a locally recorded personal lifelog, searching verbatim transcripts and temporal knowledge-graph facts, retrieving day or week summaries, gathering everything known about a person, and tracing topics over time. Answers omit timestamp filters, merge overlapping passages, and gracefully fall back to whichever store is reachable.

A server implementing Model Context Protocol that enables AI assistants to interact with Slack API through a standardized interface, providing tools for messaging, channel management, user information retrieval, and more.

Enables LLM agents to search academic literature, explore citation graphs, discover related papers, and export BibTeX using arXiv and Semantic Scholar, with prompts for evidence-grounded related-work summaries.

The Flowise MCP Server enables clients to list chatflows and call predictions, integrating seamlessly with DIY Flowise or Flowise Cloud accounts. It provides a simple interface for executing chatflows/assistants predictions with existing Flowise configurations.

Bridges NotebookLM's research capabilities with Claude's content generation, enabling creation of notebooks, deep research queries, and structured content output from URLs, PDFs, or trending topics.

Enables Claude to search an archived collection of public Telegram channel posts by keywords and semantic meaning, retrieve individual posts, view recent posts, list topics, and get archive statistics through MCP tools.

This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama

A Model Context Protocol (MCP) server that enables Claude to use Monte Carlo Tree Search algorithms for deep, explorative analysis of topics, questions, or text inputs.

Enables MCP-compatible AI clients to read local WeChat data through an existing WxLens HTTP service, so users can find messages, extract a person's statements, summarize discussions, scan multiple groups, and read related articles or attachments.

An MCP server that gives LLMs access to Wikipedia, supporting search, article retrieval, summaries, sections, and related topics across multiple languages and language variants.