"Creating a Framework Design in Draw.io" matching MCP servers:

Two prediction examples in the Alink tutorial: input a year to predict GMV; input a piece of feedback to analyze its sentiment (positive/negative).

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.

Brings YouTube capabilities to Claude Code, enabling video transcripts, search, metadata, channel info, playlists, comments, trending videos, engagement analytics, chapters, SponsorBlock filtering, and replayed heatmaps.

A service that provides HackerNews content search, retrieval and analysis through the Model Context Protocol, suitable for AI agents and developers.

Youtube, readable in AI chats.

Enables AI to send expressive stickers based on conversation context, with a built-in UI for managing stickers.

Enables creating and managing Spotify playlists using natural language with advanced similarity matching across 8 different algorithms. Supports finding similar tracks based on audio features, mood, energy, genre, and custom weighted parameters to build personalized playlists automatically.

14 tools for AI agents: transcript extraction in five formats with adjustable segment size, video metadata, video and channel search, channel browsing, in-channel search, playlists, and an asynchronous batch job for up to 4,000 transcripts. Free tier: 100 credits on signup, no card.

MCP server for reading YouTube subtitles without authentication or external binaries, using YouTube's internal get_panel endpoint to avoid rate limits and fetch full subtitles in a single request.

An MCP server that lets an AI assistant control a Kodi media player over Kodi's JSON-RPC API — transport, volume, library search, queue management, and playback history. Written in C on the GLib stack.

Tells you when your favourite football teams play and where to watch in Denmark, using data from TheSportsDB.com and built-in Danish broadcast hints.

An MCP server that enables highly personalized music recommendations from TIDAL based on custom criteria, allowing users to create and manage playlists directly in their TIDAL account.

A MCP server that implements sequential thinking protocols, provides structured problem-solving methods, decomposes complex problems into manageable steps, and supports iterative optimization and alternative reasoning paths.

Every movie showtime in San Francisco — repertory houses, single-screen neighborhood theaters, 35mm/70mm prints, and the chains — verified against each theater's own box office, with a published accuracy record. Nine read-only tools; hosted endpoint at https://scenef.com/mcp (no key), with a bundled mcp-remote bridge for stdio clients.

A server that lets you get customized music recommendations from TIDAL based on your specific criteria, allowing you to create new playlists directly in your TIDAL account.

Provides production-grade tools for YouTube channel resolution, video metadata extraction, transcripts, and playlist management. It features a quota-aware, AI-friendly design that supports structured searching and listing of public YouTube data.

Generates O'Reilly parody book covers that display directly in Claude Desktop application, allowing users to create custom covers with titles, subtitles, authors, and visual themes.

Enables AI agents to work with a user's Google Photos through Google's picker, letting users choose exactly what the agent sees while providing tools for uploading media, creating and sharing albums, writing captions and enrichments, searching app-created media, and managing multiple Google accounts.

Enables AI models to read and edit your own BandLab songs via natural-language prompts, performing concrete mix operations like adjusting track levels, pan, effects, and arrangement while creating new non-destructive revisions.

Context7 MCP is a service that provides developers with the latest code documentation and examples. By integrating into the development environment, it ensures that the code generated by LLMS is based on the latest library documentation.