YouTube Transcripts, Search & Summaries

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YouTube Transcripts MCP Server

Hosted version (no setup): apify.com/parallelstudio/youtube-transcripts-mcp. Connect any MCP client to https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp with your Apify token, pay per call. This repo is the open-source code; you can also run it locally with npm install && npm run build && node dist/index.js (stdio).

Give your AI agent YouTube transcripts, search, chapters and summaries. This MCP server fetches the captions of any public YouTube video (as plain text, timestamped segments or SRT) together with its metadata. It also searches YouTube, returns chapters, and builds structured extractive summaries where every point links to the moment it comes from.

Worked examples: four end-to-end workflows with prompts, tool calls, costs and real output are in docs/workflows.md.

It works with Claude Desktop, Claude Code, Cursor, VS Code, Windsurf and any other client that supports MCP over Streamable HTTP. You don't need a YouTube API key or a Google account. No LLM runs on the server, so you don't pay for anyone else's tokens.

What you can do with it

• Research faster. "Summarize this 2-hour podcast and give me the 10 key points with timestamps."
• Answer questions about a video. Load the transcript and let your agent quote and cite exact moments.
• Navigate long videos. Get the creator's chapters. If the video has none, get topic segments derived from the transcript.
• Find sources. Search YouTube with filters for upload date, length, sort order and "has subtitles", then pull transcripts for the best hits.
• Repurpose content. Export SRT subtitles, build show notes, or draft a blog post from a talk, using any caption language or YouTube's machine translation.

Tools

video accepts an 11-character id (dQw4w9WgXcQ) or any YouTube URL: watch?v=, youtu.be/, /shorts/, /embed/, /live/, m. and music. hosts, and youtube-nocookie.com.

All tools are read-only.

Error codes

Failures come back as MCP tool errors (isError: true). The text starts with Error (<CODE>): … and structuredContent.error holds { code, message, retryable, details }, so your agent can react to the code instead of parsing the message:

Pricing

This Actor uses pay-per-event pricing. Tool events are charged only for successful tool calls. Failed calls are not charged as tool events, whether they fail on validation, because the video is private or has no captions, or because YouTube blocks the request. Apify also charges its standard Actor start event ($0.00005 per GB of memory, minimum one event) each time a server instance starts. At the default 512 MB standby memory that's $0.00005 per start, and one running instance serves many calls before it idles out. The Pricing tab on this Actor is the authoritative list of current prices.

A search that returns zero results is still a successful call and is charged as one search event.

Connect your MCP client

Endpoint (Streamable HTTP):

https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp

Authenticate with your Apify API token by sending it as Authorization: Bearer <APIFY_TOKEN>.

Cursor (~/.cursor/mcp.json or .cursor/mcp.json)

{  "mcpServers": {    "youtube-transcripts": {      "url": "https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp",      "headers": {        "Authorization": "Bearer <APIFY_TOKEN>"      }    }  }}

Windsurf (~/.codeium/windsurf/mcp_config.json)

{  "mcpServers": {    "youtube-transcripts": {      "serverUrl": "https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp",      "headers": {        "Authorization": "Bearer <APIFY_TOKEN>"      }    }  }}

Claude Desktop (claude_desktop_config.json)

Claude Desktop's config file only launches local (stdio) servers, so bridge to the hosted endpoint with mcp-remote (needs Node.js). The same block works in any other client that only supports stdio:

{  "mcpServers": {    "youtube-transcripts": {      "command": "npx",      "args": [        "-y", "mcp-remote",        "https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp",        "--header", "Authorization: Bearer ${APIFY_TOKEN}"      ],      "env": { "APIFY_TOKEN": "<APIFY_TOKEN>" }    }  }}

Clients that can't send headers

Apify also accepts the token as a token query parameter, so a client that only takes a URL can use:

https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp?token=<APIFY_TOKEN>

Prefer the Authorization header when your client supports it: a token in a URL can end up in logs. A scoped Apify token limits the damage if it leaks.

Claude Code

claude mcp add --transport http youtube-transcripts \  https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp \  --header "Authorization: Bearer $APIFY_TOKEN"

VS Code (.vscode/mcp.json)

{  "servers": {    "youtube-transcripts": {      "type": "http",      "url": "https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp",      "headers": { "Authorization": "Bearer ${input:apifyToken}" }    }  },  "inputs": [{ "id": "apifyToken", "type": "promptString", "description": "Apify API token", "password": true }]}

Example prompts

• "Get the transcript of https://youtu.be/aircAruvnKk and explain the part about gradient descent, citing timestamps."
• "Search for talks about Rust async from the last year, longer than 20 minutes and with subtitles, then summarize the top 3."
• "Give me the chapters of this 3-hour livestream. If it has none, split it by topic."
• "Export German subtitles for this video as SRT. Translate them if there's no German track."

Four of these, with the exact tool calls, per-call costs and real output from live YouTube videos, are in docs/workflows.md:

Example outputs

The excerpts below come from the bundled fixture videos used in the test suite (see demo/transcript.md for every call and response).

get_transcript { "video": "kM3pLz8QwT0", "format": "segments", "include_timestamps": true } (trimmed):

{  "video": {    "id": "kM3pLz8QwT0",    "url": "https://www.youtube.com/watch?v=kM3pLz8QwT0",    "title": "How Solar Panels Actually Work (Explained Simply)",    "channel": "Bright Circuits",    "durationSeconds": 552,    "duration": "9:12",    "viewCount": 1843291,    "publishDate": "2025-03-14T07:00:12-07:00",    "category": "Education",    "isLive": false  },  "transcript": {    "language": "en",    "languageName": "English",    "autoGenerated": false,    "translatedFrom": null,    "matchedPreference": true,    "format": "segments",    "segmentCount": 128,    "wordCount": 870,    "truncated": false,    "segments": [      { "start": 0, "duration": 4.116, "time": "0:00", "text": "Hey everyone, welcome back to Bright Circuits." },      { "start": 4.2, "duration": 4.116, "time": "0:04", "text": "Today we're answering a question I get" }    ]  },  "availableLanguages": [    { "languageCode": "en", "languageName": "English", "autoGenerated": false, "translatable": true },    { "languageCode": "es", "languageName": "Spanish", "autoGenerated": false, "translatable": true },    { "languageCode": "en", "languageName": "English", "autoGenerated": true, "translatable": true }  ],  "translationLanguagesCount": 18}

get_video_chapters on a video with no creator chapters (auto-captions only). The chapters are derived from the transcript:

summarize_transcript { "video": "kM3pLz8QwT0", "max_points": 6 } (excerpt):

• Key points: [2:32] When a photon with enough energy hits the silicon, it knocks an electron loose and leaves a hole behind. · [5:09] Solar panels produce direct current, but your home and the electrical grid run on alternating current. · [6:52] A home battery stores surplus solar energy during the day so you can use it in the evening…
• Keywords: panels, cells, inverter, photons, solar, energy, battery, current, solar panel, electrons
• Chapter bullets use the creator's 7 chapters ("Inside a silicon solar cell", "Inverters and the grid"…), with 2 bullets each.
• Quotes: "The inverter converts direct current into alternating current that matches the grid's voltage and frequency exactly." [5:18]

How it works

Transcripts

The server fetches transcripts the same way the popular Python library youtube-transcript-api does:

1. Load the watch page. If YouTube shows the EU cookie-consent page, accept it. A reCAPTCHA page is reported as REQUEST_BLOCKED. The page also yields the InnerTube API key, the publish date, the category and any chapter markers.
2. Call the InnerTube player API with the ANDROID client context. This returns the video details and the captionTracks. The playability status is mapped to the error codes above: private, age-restricted, unavailable, unplayable, or "confirm you're not a bot".
3. Pick a track. For each preferred language in order, manual captions beat auto-generated ones, and an exact code match beats a base-language match (en-GB → en). Then download the timedtext file. The server parses srv1 XML, srv3 XML and json3.

All three requests for a video go through one proxy session, because YouTube signs caption URLs for the IP that requested them.

Getting past YouTube's IP blocks

YouTube blocks most cloud IPs. In a feasibility probe from Apify, direct requests fetched 1 of 5 test videos. With Apify's datacenter proxy, 4 of 5 worked, and the fifth video simply has no transcript. On the Apify platform this server therefore routes every YouTube request through Apify Proxy (datacenter by default), using sticky sessions and an undici ProxyAgent. When YouTube blocks a session (429, captcha, bot check, empty caption file, network error), the server discards that session and retries with a new IP, up to 5 sessions per call. A healthy session is reused for later calls.

Chapters derived from the transcript

When a video has no creator chapters, the server segments the transcript in a TextTiling style:

1. Split the transcript into 20–60 s time blocks and build a TF-IDF vector for each block.
2. At each gap between blocks, compare the vocabulary of the two blocks before it with the two blocks after it (cosine similarity). A sharp dip means the topic changed.
3. Keep the deepest dips, subject to a minimum chapter length. Then split any chapter that is still much longer than average (time-window fallback).
4. Snap each boundary to the nearest sentence start. Title each chapter with the keywords that set it apart from the other chapters, and attach its most central sentence.

Summaries without an LLM

1. Build sentences. Punctuated captions are split on punctuation. Auto-captions have no punctuation, so they are re-timed word by word and cut into short chunks at discourse markers ("so", "now", "next"…) and pauses. [Music]-style tags are removed.
2. Rank sentences with TextRank: PageRank over a graph weighted by TF-IDF cosine similarity. Very short fragments are down-weighted.
3. Choose key points, chapter bullets and quotes with MMR (Maximal Marginal Relevance), so near-duplicates don't repeat. Then put them back in chronological order.
4. Score keywords by frequency, weighted by an IDF over 1-minute windows. Unigrams already covered by a selected bigram are dropped.

The method is deterministic and transparent, and it is fast: milliseconds after the transcript is fetched. Because it quotes the speaker's own words, it can't hallucinate.

Limitations

• Public captions only. Private, members-only and age-restricted videos fail with clear error codes. The server never signs in.
• Quality depends on the captions. Auto-generated captions have no punctuation and some recognition errors. Summaries and derived chapters handle this, but creator captions give better sentences.
• Extractive, not abstractive. Summaries quote sentences from the transcript; they don't paraphrase. The stopword list and stemming are tuned for English. Other languages still work, with somewhat noisier keywords.
• Search returns videos only. Channels, playlists and Shorts shelves are excluded, and so are "People also watched" recommendations. Relative dates ("3 weeks ago") are passed through exactly as YouTube shows them.
• Unofficial endpoints. InnerTube and timedtext are the APIs YouTube's own apps use, but they are undocumented and can change. The server retries with backoff and rotates proxies. Responses are cached in memory for 10 minutes.
• Live streams. Ongoing live streams usually have no transcript until they end.

FAQ

Do I need a YouTube Data API key or a Google account? No. You only need an Apify account and token to call this hosted server.

Which languages are supported? Any language YouTube has captions for. Pass a priority list such as ["de", "en"]. If none of them exist, the best available track is returned along with a note, unless you set fallback_to_any_language: false. With translate_to, YouTube machine-translates the track.

How long can videos be? There's no fixed limit. A transcript costs one transcript event however long it is. For very long videos, use max_chars or summarize_transcript to keep your agent's context small.

Why did I get REQUEST_BLOCKED? YouTube rejected every proxy IP the server tried for that call. This is usually temporary, so retry after a short pause. Blocked calls are not charged.

Is any data stored? No. The server is stateless and keeps only a short in-memory cache. It writes nothing to datasets or key-value stores.

Can I self-host it? Yes. See below. Residential IPs can usually reach YouTube directly. On cloud servers, set YT_PROXY_URL.

Self-hosting and development

npm installnpm run buildnpm start              # MCP over stdionpm run start:http     # Streamable HTTP at http://127.0.0.1:3000/mcp (GET / and /health = readiness)npm test               # build + unit tests + MCP smoke test, all offline against recorded fixtures

On Apify (Standby mode). When APIFY_IS_AT_HOME is set, the server calls Actor.init(), forces HTTP mode, and listens on 0.0.0.0:$ACTOR_WEB_SERVER_PORT. GET / answers the Standby readiness probe and MCP is served at /mcp. YouTube traffic goes through Apify Proxy. The HTTP server has no authentication of its own: on Apify, the platform authenticates requests with your API token. If you self-host it beyond localhost, put it behind an auth proxy.

Tests

• Unit tests (test/unit/*.test.mjs, node --test) run against hand-made fixtures that mirror real YouTube responses: ANDROID player JSON, srv1/json3 timedtext, WEB search pages with continuations and shelves, watch pages including a reCAPTCHA page, and every error status. They cover parsing, track selection, description and derived chapters, TextRank and summaries, the search params encoding, error mapping, and proxy session rotation.
• MCP smoke test (test/smoke.mjs) spawns the server over stdio with YT_FIXTURES, lists the tools, calls each tool (including error paths), checks that billing charges only successful calls, checks HTTP mode and the readiness probe, and writes demo/transcript.{json,md}.
• Live remote test (test/live-remote.mjs, not part of npm test) runs against a deployed Standby URL: MCP_URL=… APIFY_TOKEN=… node test/live-remote.mjs.
• npm run fixtures regenerates test/fixtures/ from scripts/make-fixtures.mjs.

.actor/        actor.json (Standby, /mcp), input_schema.json (empty), output_schema.json (MCP endpoint)Dockerfile     apify/actor-node:20, multi-stage TypeScript build, BILLING=apifysrc/  index.ts       entry: stdio or stateless Streamable HTTP; Apify Standby wiring  server.ts      MCP tool registrations (zod schemas, error payloads, billing)  youtube.ts     watch page → InnerTube player (ANDROID) → timedtext; track selection; error mapping  transcript.ts  srv1/srv3/json3 parsing; text / SRT formatting  search.ts      InnerTube search, protobuf filter params, continuation paging  chapters.ts    description chapter parser; TextTiling-style derived chapters  text.ts        tokenizer, stemmer, sentences, TF-IDF, TextRank, keywords  summary.ts     extractive summary (key points, chapter bullets, quotes, stats)  http.ts        timeouts/retries, proxy sessions + rotation, fixture mode  proxy.ts       Apify Proxy / YT_PROXY_URL selection  fixtures.ts    offline fixture resolver  billing.ts     chargeEvent() → Actor.charge() when BILLING=apify  util.ts        error codes, cache, id/URL parsing, time helpers

Related

• App Store & Google Play Review Intelligence MCP: the same pay-per-call setup for app reviews. Your agent gets top complaints, rating by app version, regressions after a release, and side-by-side competitor comparisons for any iOS or Android app. Source: GitHub.

License

MIT