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736,277 tools. Updated 2026-11-02 15:19

"How to Get Transcripts from YouTube Videos" matching MCP tools:

  • Search for videos matching a query on YouTube (default), TikTok, or Instagram. Returns titles, ids, durations, and URLs that get_transcript accepts directly. On YouTube, upload_date, duration, sort and captions narrow the results; search_channels finds channels or playlists instead. To read what the videos say rather than only their titles, set transcripts to N: the caption transcripts of the first N rows (at most 5) come back in the same call.
    ConnectorAPI key
  • Search blobpedia's indexed Celestia talks/videos (YouTube transcripts). Celestia-specific. Returns matches across title + transcript with a short snippet around the hit.
    ConnectorNo auth
  • Get transcripts (captions) for YouTube videos, Shorts, playlists or channels as plain text and timed segments, with video metadata. Uses the captions YouTube already has; videos without captions return a failed item. Each video whose transcript comes back counts as one result on your Siftwright plan; failures are free.
    ConnectorNo auth
  • Get transcripts for TikTok videos, Instagram Reels, YouTube videos and Shorts, and X videos. Uses the platform's own subtitles when they exist and speech-to-text when they do not. Billed to your Apify account at about $2 per 1,000 subtitle transcripts ($5 per 1,000 speech-to-text ones).
    ConnectorNo auth
  • Fetch transcripts for a selected batch of videos from a YouTube channel. Choose the video count, ordering, language, and whether timestamped segments are included. This is a metered batch request.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
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    maintenance
    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.
    MIT

Matching MCP Connectors

  • Video how-to search for AI agents: 2,000+ video skills, tutorials and FFmpeg recipes. No key.

  • Transcripts from YouTube videos, whole channels and playlists for AI agents, with bulk ZIP export.

  • List the videos of a YouTube channel (id, title, duration, URL) without fetching transcripts. Accepts @handle, channel URL, or UC… channel id. Costs 1 credit.
    ConnectorOAuth
  • YouTube Shorts & Transcript Scraper: Trigger: Call this tool when an agent needs video transcripts, metadata, view counts, and audio info from short-form YouTube videos. Input: 'query' (search string), 'limit' (integer, default 10). Output: structured video details and full spoken transcripts. (x402 M2M Cost: 0.008 USDC on Base)
    ConnectorNo auth
  • This tool calls the Actor "gouda_studios/youtube-transcript-extractor" and retrieves its output results. Actor description: Get the transcript of any YouTube video or Short as clean text, timestamped text, segments and SRT. Bulk URLs, any language, auto-translate. Pay only for transcripts you get; failed videos are free.
    Connector
    Destructive
    OAuth
  • Scrape YouTube transcripts in bulk — text, timestamps, any language. Scrape YouTube transcripts in bulk — text, timestamps, any language. Videos, channels, playlists. No API key. $10 per 1,000.
    ConnectorNo auth
  • Get transcripts for a YouTube channel's most recent videos (newest first) as timestamped markdown, one section per video. Use for research across a creator's recent output; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
    ConnectorNo auth
  • Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
    ConnectorNo auth
  • Get transcripts for a YouTube channel's most recent videos (newest first) as timestamped markdown, one section per video. Use for research across a creator's recent output; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
    ConnectorNo auth
  • Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.
    ConnectorNo auth
  • Transcribe the actual audio of a YouTube, TikTok or Instagram video with Whisper large-v3. Not caption scraping: the audio is downloaded and run through speech recognition, so it works on videos with no subtitles, in any language, and on TikTok and Instagram where no caption track exists at all. Extraction runs from a real residential IP, reaching sources that refuse datacenter ranges. Returns full text plus sentence-level timestamps. — $0.020000/call, paid per request via x402 (USDC). Use when asked: "transcribe this youtube video", "get the transcript of this tiktok", "speech to text from a video URL".
    ConnectorNo auth
  • Check a transcription job. Returns status (queued / working / done / error) and metadata. Set include_transcript=true only once status is 'done' and you actually need the full text in context - transcripts of long videos are large.
    ConnectorNo auth
  • SEARCH the signed-in user's own YouTube catalogue and LIST the videos that match, by what is written in their titles, descriptions and tags. This is RETRIEVAL, not ranking: call it whenever the user wants to FIND or LIST videos rather than judge them. Use it for 'which of my videos are about X', 'show me every video where I talked about X', 'find my videos mentioning X', 'which videos have a referral or affiliate link in the description', 'list all my videos', 'what have I made about X', or any question whose answer is a SET of their videos. Also use it to pull ONE video's full record (its complete description, tags, length, views): pass that video's title as `video`. Leave everything empty to browse the whole library newest first. Results are paginated: each answer says how many matched and the `offset` to pass to see the next page, so keep asking to walk a large catalogue rather than stopping at the first page. It searches only what the creator WROTE, never what is spoken in the video. For how a video PERFORMED use analyze_video; for the best performers use find_best_videos. Needs no input: it reads their real connected YouTube channel directly. Never ask the creator anything first, not for context, not for a link, not for a title you could look up; call it immediately.
    ConnectorOAuth
  • Read the new videos the account's monitors have found, newest first: titles, links and publish times, with their transcripts for monitors that deliver them. Leave monitor_id out for every monitor. To ask again later, pass this answer's lastEventId as since and only videos found after it come back. Monitors find videos when they check, on their own schedule (check_monitor_now checks at once). Found videos are kept for 30 days. Free.
    ConnectorAPI key
  • Watch a YouTube channel or a TikTok or Instagram profile for new videos. The monitor checks on a schedule, every interval_minutes, and the new videos each check finds are read with get_new_videos (and posted to webhook_url when one is set). A monitor costs credits for as long as it exists: creating it reads the channel once for 1 credit, and every scheduled check costs 1 credit whether or not it finds anything (over a 30-day month, daily checks come to about 30 credits and hourly checks to about 720). With transcripts: true, each new video's caption transcript costs 1 credit more, and AI Fallback Transcription of one without captions 1 credit per started 5 minutes of audio. Limits: 5 monitors checked at most daily on the free plan; 100 monitors checked as often as every 15 minutes on any paid plan. Tell the user what it will cost and get their go-ahead before calling this. Channels and profiles only: a playlist or a search cannot be watched.
    ConnectorAPI key
  • YouTube Short metadata — same schema as Video Details, with isShort:true; long-form videos get HTTP 422. Costs 1 credit. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).
    ConnectorNo auth
  • Queue transcripts for MANY videos at once (up to 4000) and get a job_id back immediately — the work continues in the background. Use this instead of calling get_transcript in a loop for more than a handful of videos. Feed it video ids from list_channel_videos or list_playlist_videos (ids_only=true). Next: poll get_transcripts_job until status is 'done', reading finished transcripts from get_transcripts_results as they land. Costs 1 credit per video, charged on submit; duplicates are removed first. Requires a user key (sk_...).
    ConnectorNo auth