"styled-components" matching MCP servers:

Enables AI assistants to perform retrieval-augmented generation through MCP tools for querying knowledge hubs, listing collections, and retrieving document summaries, with pluggable ingestion, hybrid search, and evaluation components.

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

A production-grade MCP server that provides financial ML tools including RAG search, anomaly detection, contract summarization, vendor graph analysis, and model drift monitoring using entirely free, open-source components.

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

Enables Figma-to-Code workflows by retrieving and calibrating real-world components from Figma designs, screenshots, and a component knowledge base, outputting component contracts and preview implementations.

A stateless Model Context Protocol server that implements a simple echo functionality with resource, tool, and prompt components, enabling LLMs to echo back messages through standardized MCP interactions.

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.

Adds interactive widgets to LLM chats for common tasks like timers, stopwatches, unit conversions, and displaying facts. Breaks away from text-only interfaces by providing visual, interactive components similar to Google's search result widgets.

Provides LLM tools to interact with the Devici API, enabling management of threat modeling resources including users, collections, threat models, components, threats, mitigations, and teams.

A graph-based MCP server that discovers, resolves dependencies, and installs the minimal set of Claude Code components—including skills, agents, and commands—tailored to specific tasks.

Enables MCP clients and coding agents to search a local-first catalogue of existing software, packages, MCP servers, patterns, and UI components, inspect source evidence, prepare adoption briefs, and optionally edit or export React trials in a shared workbench.

Enables users to query information about LPDP scholarship financial disbursement using RAG with Pinecone vector search and Gemini 2.0 Flash, answering questions about funding components, deadlines, living allowances, and required documents.

Enables semantic search and question-answering over semiconductor component data stored in Excel files using ChromaDB vector database and HuggingFace language models through a RAG pipeline.

Automatically generates typed React hooks for Next.js projects by crawling API routes, GraphQL queries, and components. Analyzes pages to suggest optimal render modes (SSR/CSR/ISR) and produces comprehensive documentation with AI-powered guidance.

Exposes 38 tools over stdio that let an AI agent read simulated banking data, run financial and economic analyses, manage goals and preferences, and switch user contexts. It also lets the agent compose, validate, and edit declarative UI dashboards from a fixed catalog of 15 typed React components, so the interface is generated on the fly instead of hardcoded.