"Fetching historical data from tardis.dev" matching MCP servers:

Enables natural language control of Pure Data patches through Claude AI, allowing dynamic creation, modification, and DSP control via the Model Context Protocol.

Enables automated collection and downloading of multimedia content (images, GIFs, videos) from QQ channels. Features efficient video scraping, incremental updates, and intelligent fallback mechanisms for comprehensive media harvesting.

AI-native timeline editor for short-form video. Your agent cuts, captions, adds motion graphics and renders against a real, editable timeline over MCP — not a render queue. Human-in-the-loop by design: it calls request_review and waits while you supervise in a browser. Local-first and AGPL; your footage never leaves your machine.

Enables agentic interaction with vanilla Pure Data by providing tools for live patch creation, inspection, and manipulation via an MCP server that synchronizes with a Pd bridge patch.

A Model Context Protocol server that enables fetching and processing images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings with proper MIME types.

An MCP server that extracts rich metadata (title, description, duration, chapters, subtitles, statistics, etc.) from media URLs across thousands of sites using yt-dlp, and also provides transcript fetching and search capabilities.

Enables fetching, searching, and analyzing YouTube video transcripts in multiple languages using yt-dlp. Supports timestamp filtering, language detection, and transcript summaries with robust error handling for production use.

Enables fetching YouTube video transcripts with metadata, including timed captions in multiple formats (JSON, SRT, VTT, CSV, TXT) and preprocessing options.

An MCP server for intelligent YouTube video analysis that provides token-optimized summaries, sentiment analysis, and entity extraction from transcripts. It enables AI assistants to perform video reporting, channel monitoring, and comprehensive YouTube searches through structured data tools.

MCP server for generating and editing images using OpenAI, and creating videos using OpenAI Sora and Google Veo. Enables fetching media from URLs or disk with smart output placement.

An MCP server that uses Puppeteer and headless Chrome to scrape YouTube transcripts directly from the video page UI. It provides tools for fetching plain text transcripts, timed segments with deep links, and video metadata while bypassing standard API rate limits.

Enables creating and polling Luma video modification tasks, fetching task status, and checking pricing via the RunAPI API.

Control and live-patch Pure Data from AI agents via the Model Context Protocol.

An MCP server that extracts transcripts, metadata, and summaries from YouTube videos across various URL formats including Shorts and standard links. It provides comprehensive video data and insights for analysis within MCP-compatible environments.

Enables users to fetch transcripts and comments from public Loom video URLs. It provides tools to retrieve video text data and discussion threads directly through the Model Context Protocol.

Enables driving TouchDesigner from any MCP client during live rendering, with safe never-overwrite saves, GPU health measurement, and 67 tools for node, parameter, data, and timeline control.

A Bilibili subtitle fetching MCP server that supports various input formats (BV number, video URL, short link) and offers configurable language preferences, output formats, and ASR fallback.

MCP server for downloading Instagram content (videos, reels, audio, carousels) using yt-dlp, with tools for downloading media and fetching metadata. Supports stdio and HTTP transports.

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

A Claude Code MCP server that converts saved articles into AI-generated conversational podcasts tailored to user interests. It operates locally, fetching articles, generating dialogue scripts using Claude's LLM, and synthesizing audio through various TTS providers.