Scraping YouTube Videos by Keyword

Raw YouTube video dataset for any search query. Returns video-level metadata including engagement metrics and channel info.

Prerequisites

APIFY_TOKEN environment variable set
Optional: Apify MCP server installed

Inputs

Parameter	Type	Required	Default	Notes
`startUrls`	array	Optional	`[]`	YouTube URLs — channels, playlists, Shorts, search results
`youtubeHandles`	array	Optional	`[]`	YouTube channel handles (e.g. `@kurzgesagt`)
`getTrending`	boolean	Optional	`false`	Retrieve trending videos
`keywords`	array	Optional	`[]`	Search keywords
`gl`	string	Optional	`us`	Country code for results (e.g. `US`, `GB`)
`hl`	string	Optional	`en`	Language code (e.g. `en`, `de`)
`uploadDate`	string	Optional	`all`	Upload date filter: `any`, `hour`, `today`, `week`, `month`, `year`
`duration`	string	Optional	`all`	Duration filter: `any`, `short`, `long`
`features`	string	Optional	`all`	Feature filter: `4k`, `hd`, `live`, `cc`, `3d`, `hdr`, etc.
`sort`	string	Optional	`r`	Sort order for search results
`maxItems`	number	Optional	Unlimited	Maximum videos to return
`customMapFunction`	string	Optional	—	JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Build search query
- [ ] Step 2: Run youtube-scraper
- [ ] Step 3: Poll for SUCCEEDED
- [ ] Step 4: Deliver video dataset

Step 2: Run the Actor

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~youtube-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~youtube-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~youtube-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~youtube-scraper"
Input:
{
  "searchKeywords": "<query>",
  "maxResults": 50,
  "sortBy": "relevance"
}

REST API fallback:

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchKeywords": "<query>", "maxResults": 50}'

Save id as RUN_ID. Poll until status = SUCCEEDED:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID?token=$APIFY_TOKEN" | grep '"status"'

Fetch results:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN&format=json"

Step 3: Handle Edge Cases

< 20 results: Query may be too narrow; broaden search term.
Age-restricted content in results: These may have limited metadata — flag rows with missing viewCount.
Duplicate video IDs: Deduplicate by videoId.

Output Format

# YouTube Video Dataset: "<query>"
Videos collected: N | Sort: <sortBy>

| Video ID | Title | Channel | Views | Likes | Comments | Duration | Published |
|----------|-------|---------|-------|-------|----------|----------|-----------|
| ...      | ...   | ...     | ...   | ...   | ...      | ...      | ...       |

Available fields: videoId, title, channelName, channelId, viewCount, likeCount,
commentCount, duration, publishedAt, videoUrl, thumbnailUrl, description

Troubleshooting

Fewer results than requested: YouTube search may have limited results for niche queries. Missing like counts: YouTube hides dislikes but likes are still available; some videos hide all counts.

scraping-youtube-videos-by-keyword