"mcp server fetch" matching MCP servers:

Enables AI assistants to fetch YouTube video transcripts with precise timestamps, multi-language support, and time-range filtering.

Enables downloading videos from 1000+ platforms including YouTube, Bilibili, TikTok, and Twitter using yt-dlp. Supports both MCP protocol and REST API modes with real-time progress tracking, multiple formats, and subtitle downloads.

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 AI assistants to fetch and analyze transcripts from YouTube videos using video IDs or URLs, with support for multiple language preferences.

Enables AI assistants and MCP clients to fetch YouTube video captions with timestamps, title, channel, and available languages, and to export transcripts as text, SRT, or WebVTT. It works with watch, Shorts, youtu.be, embed links, or bare video IDs without an API key.

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.

Enables AI agents to fetch transcripts, metadata, and download videos/audio from YouTube without API keys.

MCP server for YouTube that provides tools to fetch video metadata and transcripts, enabling natural language queries about YouTube videos.

Enables AI assistants to fetch and process YouTube video transcripts in multiple formats and languages, with built-in caching and rate limiting for efficient video content analysis.

Enables MCP clients and agents to fetch YouTube transcripts and caption lists from video IDs or links, preferring manual/auto captions by ordered language preference and falling back to local Faster-Whisper audio transcription when captions are unavailable. Results include source, language, full text and timestamped segments, with CLI exports to JSON, text, SRT and WebVTT, all without paid APIs or API keys.

Enables MCP-aware agents to fetch direct captions or download audio and transcribe with local Whisper from common video platforms like YouTube, Vimeo, and Twitch.

Enables AI assistants to fetch YouTube video metadata, chapters, and timestamped transcripts (including paginated and language-specific caption retrieval) so they can produce summaries, study notes, comparisons, and source-referenced answers. The returned transcript evidence also carries explicit coverage status, letting the assistant know when a transcript is partial or unavailable.

Enables an AI assistant to fetch a YouTube video's captions on demand, returning every line prefixed with its start time so the assistant can quote the video and point to the exact moment something was said.

Enables AI assistants like Claude, Cursor, and Codex to clip YouTube, Twitch, and Kick videos or live streams (downloading locally via yt-dlp), create beat-synced edits, and generate AI Studio images and video, then fetch rendered clips, captions, and post drafts. It also exposes account credits, project status, and media uploads, while never purchasing anything or publishing on the user's behalf.

Enables AI agents to find meme and reaction clips via the Vlipsy API or local folders, look at them as contact-sheet images, and fetch or convert them into rendered assets with attribution sidecars. It also drops those clips into ffmpeg renders and editing timelines (OTIO, FCPXML, Premiere XML, EDL) or returns paste-ready Remotion, HyperFrames, MoviePy and HTML snippets.

Enables AI assistants to automatically fetch and analyze trending content from Reddit, YouTube, and News, then turn it into finished scripts, cloned-voice audio, and talking-head videos through single composite tool calls. Context is injected automatically via prompts and resources, so no manual tool chaining is needed for research, scriptwriting, or full video production.

Exposes ComfyUI workflows as 12 MCP tools on ComfyUI's own port, letting AI agents generate, edit, and remove backgrounds from images plus create videos by passing semantic parameters instead of whole workflow graphs. Agents can list models, submit and track async tasks, fetch artifact URLs, and jump to a visual asset/task page.

Enables ChatGPT conversations to fetch available captions and metadata from video IDs, URLs, creator uploads, playlists, chapters, and time ranges, returning cleaned Markdown or paginated cues. Cached snapshots, isolated per-video failures, and an outbound-only acquisition worker keep retrieval self-hosted without paid APIs or cookies.