"YouTube fashion content finder for trends and style guides" matching MCP servers:

Enables AI assistants to query YouTube search trend data, including rising topics, video keyword growth, and historical demand, using plain language.

Enables AI assistants to query YouTube search trends, including rising topics, growth metrics, and historical search demand, using natural language.

Enables AI-powered YouTube content management using Claude Code to orchestrate research, scripting, and scheduling via Google Sheets, Docs, and Drive.

Provides read-only access to Homechecker's Australian residential-building guidance corpus, with tools for listing, searching, retrieving guides, and generating buyer checklists.

Enables style verification and CSS inspection through Chrome DevTools Protocol, using JSON specs to check computed styles, find elements, and interact with pages.

A Model Context Protocol (MCP) server that provides YouTube Data API v3 integration for content discovery and analytics. It enables AI assistants to search for videos, channels, playlists, and retrieve detailed metrics.

Enables AI assistants to search YouTube for videos, channels, and playlists while retrieving detailed analytics and metrics through the YouTube Data API v3. Supports advanced filtering options and provides comprehensive statistics for content discovery and analysis.

Enables natural-language shopping queries on a fashion inventory flat file, with tools for searching products and recommending matching items via OpenAI.

A fashion vertical MCP server providing tools for product SEO audits and trend analysis to integrate with AI agents like Claude, Cursor, and Codex.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Provides access to step-by-step drawing tutorials from easydrawingguides.com, enabling users to search for drawing guides, retrieve detailed tutorial content in Markdown format, and browse categories for artists of all skill levels.

Real-time trend data from Google Trends (Search, Images, News, Shopping), YouTube, TikTok, Reddit, Amazon, Wikipedia, npm, Steam, Spotify, X (Twitter), App Store, Google Play, web traffic, and news sentiment via one MCP connection. Works with Claude, Cursor, VS Code, Windsurf, ChatGPT, and any MCP-compatible AI.

Analyzes a codebase to extract its coding conventions and exposes tools via MCP for AI agents to retrieve live style rules, ensuring generated code matches the project's unwritten style.

Live trend data for your AI. 25+ platforms. One connection.

Enables AI agents to query live trend data and historical search volume across 30+ platforms like Google, TikTok, YouTube, Amazon, and Reddit, including growth comparisons and top-ranking trends.

Provides deterministic design style recommendations and structured tokens for AI content generation, with 30 curated styles including color palettes, typography, and visual directives.

Extracts YouTube video metadata, titles, and descriptions along with transcripts generated from subtitles or OpenAI Whisper speech-to-text. This server enables users to retrieve and analyze detailed video content directly within MCP-compatible environments.

A tiny local MCP server that learns a user's conversational style, catchphrases, dialect markers, emoji habits, tone preferences, and concrete collaboration preferences without storing private memories.

Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.

A MCP server that aggregates hot trends and rankings from various Chinese websites and platforms including Weibo, Zhihu, Bilibili, and more.