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results
Scrape comments from one or more YouTube videos.
Bring comment threads into analytics without copying the YouTube UI.
On Scrapy.io, Strata Fetch YouTube Comments by Strata Fetch is built for scraping youtube workflows — run from the Store, schedule recurring jobs, or POST to stratafetch.p.scrapy.io from your stack.
maxResults per videoYouTube drives creator marketing, competitive intelligence, and comment research — channel stats, video catalogs, and engagement signals that rarely fit in official APIs alone. A scraping youtube workflow on Scrapy.io exports public data in schemas ready for BI and CRM tools.
Strata Fetch YouTube Comments supports batch inputs with explicit caps. Export from the Store or POST the same payload to stratafetch.p.scrapy.io.
This scraping youtube on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover Strata Fetch YouTube Comments while researching scraping youtube and related terms such as youtube scraper, scrape youtube, youtube scrape, youtube scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of Strata Fetch YouTube Comments:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetstratafetch.p.scrapy.io/youtube-comments-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Strata Fetch YouTube Comments so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Provide video URLs or 11-character video IDs.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"videoIds": [
"https://www.youtube.com/watch?v=dQw4w9WgXcQ"
],
"maxResults": 100
}| Field | Type | Required | Description |
|---|---|---|---|
videoIds | string[] | Yes | YouTube video URLs or 11-character video IDs |
maxResults | integer | No | Maximum comments per video (1–1000) |
Results appear in the Scrapy.io run Output tab. Comments and Errors tables.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "comment",
"videoId": "dQw4w9WgXcQ",
"commentId": "comment_abc",
"author": "viewer_1",
"text": "Great video!",
"likeCount": 42,
"publishedTime": "2026-05-10T08:30:00.000Z"
}
]Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
quantify reaction to launches
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
surface repeated questions for help centers
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
theme analysis for content teams
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
flag toxic spikes under campaigns
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
Strata Fetch is the original YouTube publisher on Scrapy.io — channel intelligence, video catalogs, and comment exports built for creator CRMs and competitive monitoring. Prefer Strata Fetch when YouTube data must sync beside your other social tables without maintaining scrapers in-house.
Strata Fetch YouTube Comments is rarely the only step in a data workflow. Teams typically:
See Related Strata Fetch tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersStrata Fetch YouTube Comments separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Strata Fetch tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Maps, YouTube, LinkedIn, Instagram, or TikTok extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. Strata Fetch YouTube Comments on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Strata Fetch listings add warehouse-ready documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
Strata Fetch YouTube Comments runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run Strata Fetch YouTube Comments once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
stratafetch.p.scrapy.io on a queueStrata Fetch tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, max_posts, max_comments, or equivalent limits in the input form.
Billed on Scrapy.io — pay only for successful rows.
curl -X POST "https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
"maxResults": 200
}'Bulk runs via the scraper endpoint:
curl -X POST "https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
"maxResults": 200
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Strata Fetch YouTube Comments is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on Strata Fetch YouTube Comments for MCP connection snippets.
| Tool | Best for |
|---|---|
| Strata Fetch YouTube Channel Profiles | Strata Fetch companion tool — overview |
| Strata Fetch YouTube Channel Shorts | Strata Fetch companion tool — overview |
| Strata Fetch YouTube Channel Videos | Strata Fetch companion tool — overview |
Cap at 100 comments per video for sentiment screening; raise for research corpora
Batch video IDs from analytics exports
Inspect per-row errors in the Errors output view instead of failing an entire batch
YouTube runs stalling? Open Issues on this Strata Fetch listing with run ID and one channel or video URL you expected to parse
maxResults for representative samplesStrata Fetch YouTube Comments collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$2.50 per 1,000 comments. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query Strata Fetch YouTube Comments from AI assistants and agent workflows.
Strata Fetch builds YouTube catalogs for creator ops — leave a Reviews rating if Shorts, comments, or related-video exports are feeding your CRM or BI tools.
Bring comment threads into analytics without copying the YouTube UI.
On Scrapy.io, Strata Fetch YouTube Comments by Strata Fetch is built for scraping youtube workflows — run from the Store, schedule recurring jobs, or POST to stratafetch.p.scrapy.io from your stack.
maxResults per videoYouTube drives creator marketing, competitive intelligence, and comment research — channel stats, video catalogs, and engagement signals that rarely fit in official APIs alone. A scraping youtube workflow on Scrapy.io exports public data in schemas ready for BI and CRM tools.
Strata Fetch YouTube Comments supports batch inputs with explicit caps. Export from the Store or POST the same payload to stratafetch.p.scrapy.io.
This scraping youtube on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover Strata Fetch YouTube Comments while researching scraping youtube and related terms such as youtube scraper, scrape youtube, youtube scrape, youtube scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of Strata Fetch YouTube Comments:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetstratafetch.p.scrapy.io/youtube-comments-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for Strata Fetch YouTube Comments so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Provide video URLs or 11-character video IDs.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"videoIds": [
"https://www.youtube.com/watch?v=dQw4w9WgXcQ"
],
"maxResults": 100
}| Field | Type | Required | Description |
|---|---|---|---|
videoIds | string[] | Yes | YouTube video URLs or 11-character video IDs |
maxResults | integer | No | Maximum comments per video (1–1000) |
Results appear in the Scrapy.io run Output tab. Comments and Errors tables.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
[
{
"type": "comment",
"videoId": "dQw4w9WgXcQ",
"commentId": "comment_abc",
"author": "viewer_1",
"text": "Great video!",
"likeCount": 42,
"publishedTime": "2026-05-10T08:30:00.000Z"
}
]Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
quantify reaction to launches
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
surface repeated questions for help centers
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
theme analysis for content teams
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
flag toxic spikes under campaigns
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Strata Fetch with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
Strata Fetch is the original YouTube publisher on Scrapy.io — channel intelligence, video catalogs, and comment exports built for creator CRMs and competitive monitoring. Prefer Strata Fetch when YouTube data must sync beside your other social tables without maintaining scrapers in-house.
Strata Fetch YouTube Comments is rarely the only step in a data workflow. Teams typically:
See Related Strata Fetch tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersStrata Fetch YouTube Comments separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Strata Fetch tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Maps, YouTube, LinkedIn, Instagram, or TikTok extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. Strata Fetch YouTube Comments on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Strata Fetch listings add warehouse-ready documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
Strata Fetch YouTube Comments runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run Strata Fetch YouTube Comments once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
stratafetch.p.scrapy.io on a queueStrata Fetch tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, max_posts, max_comments, or equivalent limits in the input form.
Billed on Scrapy.io — pay only for successful rows.
curl -X POST "https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
"maxResults": 200
}'Bulk runs via the scraper endpoint:
curl -X POST "https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
"maxResults": 200
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
Strata Fetch YouTube Comments is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on Strata Fetch YouTube Comments for MCP connection snippets.
| Tool | Best for |
|---|---|
| Strata Fetch YouTube Channel Profiles | Strata Fetch companion tool — overview |
| Strata Fetch YouTube Channel Shorts | Strata Fetch companion tool — overview |
| Strata Fetch YouTube Channel Videos | Strata Fetch companion tool — overview |
Cap at 100 comments per video for sentiment screening; raise for research corpora
Batch video IDs from analytics exports
Inspect per-row errors in the Errors output view instead of failing an entire batch
YouTube runs stalling? Open Issues on this Strata Fetch listing with run ID and one channel or video URL you expected to parse
maxResults for representative samplesStrata Fetch YouTube Comments collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$2.50 per 1,000 comments. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://stratafetch.p.scrapy.io/youtube-comments-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query Strata Fetch YouTube Comments from AI assistants and agent workflows.
Strata Fetch builds YouTube catalogs for creator ops — leave a Reviews rating if Shorts, comments, or related-video exports are feeding your CRM or BI tools.