"Material Design Icons" matching MCP servers:

lucide-icons-mcp

Enables AI assistants to search and retrieve structured video material, including dialogue, jokes, story structure, and video details through natural language queries.

Enables an assistant to answer questions solely from a curated corpus of public-domain women-authored texts, with citations and explicit no-coverage status when the corpus lacks material.

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.

heroicons-mcp is a Model Context Protocol (MCP) server that exposes Heroicons. It allows LLMs and agentic applications to search, list, and generate usage examples of icons in React applications.

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

Enables users to create and control portable, user-owned memory archives, including saving memories, reflections, values, and stories, exporting them as open JSON, publishing or discovering public archives, and loading consented material as a clearly-labelled memory-based AI persona.

An MCP-native evidence retrieval platform that ingests source material, builds lexical and vector indexes, performs hybrid retrieval, and returns structured evidence packages for AI assistants.

MCP server for creating and managing Mindola lenses, which are grounded AI pages that answer questions from your own material with citations. Enables AI assistants to create lenses, add knowledge, and monitor status through natural language.

Enables coding agents to ground UI work in real product screens by retrieving real screen references, fonts and icons, and recorded design systems, while also serving bundled design-workflow resources, playbook prompts, and connection diagnostics without a token.

Provides AI coding agents with structured access to design research, component libraries, motion systems, design DNA extraction, visual search, and production workflows through MCP and SDK interfaces.

Gives AI agents persistent, shared memory by ingesting notes, code, transcripts, and session captures, then serving token-optimized context and hybrid keyword/semantic search over MCP and REST. Agents can classify, promote, and synthesize stored material so each session builds on prior work instead of starting from zero.

Lets coding agents index and search local PDF books, retrieve relevant passages with citations, and persist design lessons for system design and implementation tasks.

Enables Cursor to access Figma files through the Model Context Protocol, enhancing its ability to accurately interpret and utilize design data for code generation.

Enables coding agents to query a private, curated design reference library over MCP, retrieving approved screenshots alongside the owner's take-and-avoid notes, marked component regions, and brand kits with colors, typography and CSS. Supports ranked recommendations by design brief, filtered search, and component lookup so agents can ground their implementation choices in saved preferences.

Enables natural language interaction with KiCad projects, schematics, and PCBs, supporting project management, design rule checking, netlist extraction, and datasheet RAG search.

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 clients to semantically search a local folder of markdown documents via a single search_notes tool, with embeddings generated locally by Ollama and support for excluding superseded or archived material.

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.

Exposes roughly forty tools over streamable HTTP so AI assistants can search an archive of sourced evidence, time series, forecasts, slides and datasets, reuse existing material with its citations, and write new sourced findings back. It also covers slide and deck management, feedback, photo and dataset access.

Enables AI assistants like Cursor and Claude Desktop to access a local AI Material Cabinet for searching, reading/writing content, creating documents, and retrieving chunks via MCP.

Enables coding agents to ground UI work in real product screens by returning concrete screen references as inline images, licensed fonts, icons, and the colors, typography, and components behind a chosen web screen. It also serves token-free design-skill documents, command playbook prompts, and connection diagnostics.

Enables intent-based semantic search over external design system documentation, allowing MCP-compatible AI assistants to retrieve relevant design tokens, component architectures, and code patterns via a single tool.

Gives coding agents real product screen references, design-system sections, and font/icon materials as inline images and typed structured content, so unresolved layout, state, or typography questions can be grounded in screens that already exist. It also serves a bundled design workflow, command playbooks, and connection diagnostics that work without a token.

Enables identification of BSN SKU/material and real-time inventory availability through natural language queries and vector search.

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

Enables coding agents to ground UI work in real product screens by finding concrete screen references and design materials for unresolved layout, state, interaction, font, or icon questions. Also retrieves the recorded design systems behind chosen web screens and reports local connection status.

Enables other agents to search confirmed project knowledge, ingest source material, submit evidence-backed candidate memories, compile wiki content, and resume persistent conversations through shared local sessions and recall without duplicating the database.

Exposes the compiled knowledge base via the Model Context Protocol to external AI clients. This allows agents to query the wiki and receive cited, Markdown-formatted answers grounded in the source material.

A Model Context Protocol server that generates production-ready React components using the Reablocks design system through natural language processing.

Enables AI agents to answer SEO, local SEO, blogging, and Etsy questions strictly from a governed knowledge base of cited course material, declining anything outside its scope.

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.

Provides semantic search over AWS Cloudscape Design System documentation using natural language queries, enabling AI assistants to efficiently find and retrieve component documentation with token-efficient responses.

Enables AI agents to browse, search, and read a curated library of 198 UI/UX and animation design skills across 17 categories, distilled from 10 open-source projects, with a progressive 5-step workflow for guidance.

Lets MCP clients search vetted public listings and their own private library of coding-agent sessions, load a saved session as bounded starting context, and save the current transcript privately, reusing an existing command-line sign-in. Sessions are scrubbed and framed as untrusted reference material, and acquiring a paid listing never completes a purchase automatically.

A persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.

An MCP server that ingests semiconductor PDFs into a Neo4j knowledge graph, enabling AI agents to query domain knowledge, verify claims against source text, and record design reasoning.

A lightweight server that provides curated, high-quality prompts for common development tasks like UI/UX design, project setup, and debugging to enhance AI-powered development workflows.

Provides AI-powered theatrical lighting design capabilities for the LacyLights system, allowing users to generate lighting scenes, analyze scripts, manage cues, and optimize lighting effects based on artistic intent.

Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.