View in the ChatGPT registry- Brand
- TubeLab
- Category
- Data & Analytics
- Primary Subcategory
- Pending
Integration details
Description
TubeLab gives ChatGPT read-only access to public YouTube data, enriched for niche research and ideation. Typical uses: finding unsaturated niches; competition research; outlier ideation; video summarization; analysing video comments for content ideas. 12 tools cover: • Channel Search: filter YouTube channels by recency, view count, subscribers, upload volume, consistency, language, estimated audience (region, age, gender, income), revenue, RPM and 40+ filters • Related Channels: find channels similar to any channel, ideal for competition research • Outlier Videos Search: search videos going viral in your niches, great for ideation • Related Outliers: search viral videos similar to another video • Trending Formats: the title formulas working right now in any niche, with the videos that used them and how fast they are spreading • Videos: title, description, keywords, view and like counts and all metadata • Channels: profile, videos and shorts. Takes a channel ID, URL or @handle • Transcripts: caption text with timestamps, in the available language • Comments: get a sample of 100 comments of a video TubeLab is read-only. It cannot publish, subscribe, or moderate anything on YouTube.
- Integration type
- Plugin
- Verification status
- Not applicable
- Platform
- ChatGPT
- Primary Subcategory
- Pending
- Secondary Subcategories
- None listed
- Brand
- TubeLab
- Access
- Account required
- First tracked
- 2026-10-08
- Tool count
- 12
- Geography
- US
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
Agent DiscoverabilityChatGPT Plugin Discovery ScoreYour score is coming
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What discovery looks like
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Competitive lineup
12 tools agents can invoke
TubeLab ChatGPT Plugin FAQ
How the directory, categories and Discoverability Score work.
Read the methodologyHow do I improve TubeLab's ChatGPT Plugin discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.