"Material Design" matching MCP servers:

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.

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

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.

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.

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 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documents via a single search_notes tool, with embeddings generated locally by Ollama and support for excluding superseded or archived material.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 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 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.

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.

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.