YouTube Scraper — Video Metadata, Transcripts & Comments

Extract YouTube video data at scale without an API key or quota limits. This YouTube scraper covers video metadata, keyword search results, channel upload feeds, full video transcripts (including auto-generated captions), and top comments — all in one actor with pay-per-result pricing.

Whether you need to monitor a competitor's channel, feed transcripts into an LLM pipeline, or track video engagement across a topic, this scraper gives you clean structured data with a parse_confidence quality score on every record.

Why use this YouTube scraper instead of the YouTube Data API?

The official YouTube Data API v3 has a daily quota of 10,000 units. A single search call costs 100 units — that's 100 searches per day on the free tier. This actor calls YouTube's internal InnerTube API and parses ytInitialData / ytInitialPlayerResponse directly, with no quota cap and no API key setup.

What you get — 5 scrape modes

• video_details — Full metadata for one or more YouTube videos
• search — Keyword search results with ranking position
• channel_videos — All recent uploads from a YouTube channel
• transcript — Full transcript text with timestamps (auto-generated + manual captions)
• comments — Top comments for a video

Features

• 5 modes: video_details, search, channel_videos, transcript, comments
• No API key: Uses YouTube's internal InnerTube API and HTML parsing
• Transcripts: Full text with timestamps via youtube-transcript-api (handles auto-generated captions)
• parse_confidence: Every record includes a quality score (0.0–1.0) — Apify's daily canary catches silent failures
• PPE pricing: Pay only for results scraped (video-result event per record)

Modes

video_details

Full metadata for one or more YouTube videos.

Input: videoUrls — list of YouTube URLs or bare video IDs.

Output fields: video_id, title, channel, channel_id, views, published, duration_seconds, duration_raw, description, tags, thumbnail, thumbnails, video_url

search

Search YouTube by keyword and return video results.

Input: searchQueries — list of search terms.

Output: Same schema as video_details plus relative published (e.g. "3 weeks ago").

channel_videos

List recent uploads from a YouTube channel.

Input: channels — handles (@freeCodeCamp), channel IDs (UCxxx), or full URLs.

Output: video_id, title, views, published (relative), duration_raw, thumbnail

transcript

Extract full transcript text from a video.

Input: videoUrls, optional transcriptLanguage (default: en).

Output: transcript_text (full joined text), language, is_generated, segment_count

Note: Falls back to auto-generated captions in any language if the requested language is unavailable.

comments

Fetch top comments for a video.

Input: videoUrls, optional maxComments (default: 20).

Output: comment_id, author, text, likes, is_pinned

Proxy

YouTube tolerates datacenter IPs for metadata scraping. Use Apify Proxy (residential) at high volume or if you encounter blocks. Leave proxyConfiguration empty for no proxy.

parse_confidence

Every record includes a parse_confidence field (1.0 = all expected fields present, 0.0 = critical failure). If YouTube changes its HTML structure, confidence drops — giving you a machine-readable drift signal before buyers notice.

Pricing

PPE event: video-result — one charge per record pushed.

Technical notes

• Video metadata: parse ytInitialPlayerResponse from watch-page HTML (no API key needed)
• Search: InnerTube POST /youtubei/v1/search with WEB client context
• Channel videos: parse ytInitialData lockupViewModel from channel page HTML
• Transcripts: youtube-transcript-api library (handles PoToken internally)
• Comments: InnerTube POST /youtubei/v1/next + frameworkUpdates.entityBatchUpdate entity store

Frequently asked questions

Does this YouTube scraper work without an API key?

Yes. The actor uses YouTube's internal InnerTube API and HTML parsing — no API key, no Google Cloud project, no quota limits to manage.

Can I scrape YouTube transcripts for multiple videos at once?

Yes. Pass a list of video URLs or video IDs to videoUrls. Each video generates one transcript record with the full joined text, language code, and whether it's auto-generated.

What happens if a video has no transcript?

The actor sets parse_confidence below 1.0 and includes a warnings entry. Your downstream pipeline can filter on parse_confidence rather than crashing on missing fields.

Is proxy needed?

YouTube tolerates datacenter IPs for most scraping. Leave proxyConfiguration empty for no proxy. At high volume or if you hit CAPTCHAs, switch to Apify RESIDENTIAL proxy.

How is pricing calculated?

This actor uses pay-per-result (PPE). One charge (video-result event) per record pushed to the dataset. Failed lookups, retries, and probe requests are not charged.

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Not affiliated with YouTube or Google.

Integrations

Built for content researchers, competitive analysts, and LLM-pipeline builders extracting video metadata, transcripts, and comments at scale — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.