"Resources for React TypeScript UI Components" matching MCP servers:

An MCP server that connects AI assistants to a Neo4j graph database, enabling querying of movie data through tools like graph statistics, genre-based search, and movie details, along with advanced features such as LLM sampling and completions.

Provides comprehensive filesystem operations, text search/replace, image processing, and Tesseract OCR capabilities for AI agents via the Model Context Protocol.

MCP server for the ReactUse library. Exposes 110+ React Hook signatures, examples, and API metadata so AI coding assistants can discover and use any hook from @reactuses/core directly.

Provides comprehensive documentation for MAX Platform, including Bot API endpoints, guides, Bridge API, and UI components, via MCP tools and resources for AI coding agents.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

Provides programmatic access to Material Web documentation and components for AI agents, enabling documentation search, template generation, and HTML validation.

Provides AI assistants access to live Material Design 3 documentation including Foundations, Styles, and Components, returning official content as Markdown.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Provides access to PatternFly React documentation, development rules, and component schemas through MCP tools, enabling AI assistants to help developers build applications with PatternFly components following best practices.

Enables LLMs to access MCP protocol specifications and TypeScript SDK documentation with context-aware search and code templates for building custom MCP servers.

A minimal TypeScript starter template for building Model Context Protocol (MCP) servers with auto-loading architecture for tools, resources, and prompts. Includes code generators, dual transport support (stdio/HTTP), and production-ready structure.

Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.

Enables AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.

MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resources for client-side exploration.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.