YouTube comments,
ready for your code and AI.
Extract public comments, replies, and transcripts from a YouTube video URL as structured JSON. Sort by top or newest, paginate through comments, load reply threads, and get timestamped transcripts.
Read our field report: How to Scrape YouTube Comments in 2026 (and Why You Should).
TypeScript / JavaScript? Use the open-source SDK: on npm · Source on GitHub
Trusted by developers shipping real products.
98,250 served today
Request
$ curl -X POST https://api.fetchlayer.dev/youtube/comments \ -H "Authorization: Bearer ss-your-key" \ -H "Content-Type: application/json" \ -d '{"videoUrl":"https://youtube.com/watch?v=...","sort":"newest"}'
Response
[
{
"username": "@viewer",
"comment": "Please cover offline mode next.",
"likes": 42,
"hasReplies": true,
"date": "1 day ago"
}
] Built for feedback workflows
Fetch the public signal. Use it wherever your team works.
Public video comments
Provide a public YouTube video URL and retrieve the visible comment conversation as structured JSON.
Top or newest
Prioritize the most engaged feedback or focus on the latest reaction to a new video, launch, or announcement.
Nested replies
Control reply depth when the valuable signal is in the conversation below a top-level comment.
Audience research
Find repeated questions, objections, praise, and content requests in the comments your audience leaves publicly.
AI-ready JSON
Send comments to an LLM or MCP agent to summarize viewer sentiment, group themes, and surface pain points.
Your workflow, your schedule
Call the endpoint from your own code, cron job, or automation when you need another fresh snapshot of the discussion.
Analyze YouTube comments with AI—then export the results to CSV.
Paste a video URL into FetchLayer Research Chat and ask what the audience is saying. It can surface recurring questions, pain points, sentiment, and content requests while keeping the source comments in a reusable file.
- ✓Ask questions in plain English
- ✓Analyze themes, sentiment, and pain points
- ✓Download the structured results as CSV or JSON
No code or setup required · Uses your FetchLayer credits
Analyze the comments on this YouTube video. Find recurring questions, pain points, and content requests, then export the comments and themes as CSV.
I found four recurring questions and three strong follow-up content ideas. The comment-level themes, engagement, and source context are organized in the export.
youtube-comment-analysis.csv
284 comments · 7 columns · ready to download
Solutions
Build the workflow around the feedback.
Analyze YouTube comments
Find recurring questions, objections, content requests, and audience sentiment from the source conversation.
Explore →Research your audience
Use public comment language to guide content ideas, market research, and competitor analysis.
Explore →Add App Store reviews
Bring public customer reviews into the same feedback and AI workflow.
Explore →From raw feedback to action
One request is the start of the workflow.
Store the structured response, run it on a schedule, pass it to an LLM, or feed it into the system your team already uses. FetchLayer handles retrieval so you can focus on the outcome.
- 01
Provide a video URL
Use the public URL for the video whose comments you want to understand.
- 02
Choose the view of the conversation
Set top or newest sorting, the reply depth you need, and how far to scroll for more comments.
- 03
Analyze or act on the signal
Store the comments, run your own monitoring workflow, or ask an AI agent to identify the useful patterns.
MCP & agents
Your AI already knows
how to use this.
Use the YouTube endpoint directly from your MCP-compatible agent. Ask it to retrieve public feedback, identify patterns, and turn the result into a useful brief without writing integration glue.
Pick your editor and we hand you the config with your key already in it — no JSON to hand-edit, no wrapper code.
Get your free API keyFree tier · no credit card · any MCP host
Read the newest comments on this product video. What questions keep appearing, what do viewers dislike, and what follow-up video should the creator make?
The discussion is broadly positive, but the repeated request is a step-by-step setup walkthrough. Viewers also ask whether the product supports offline use and team collaboration.
Works with every MCP-compatible tool
Use cases
What developers build with YouTube comment data.
Same API, endless applications. Here is what teams ship with public audience feedback.
Audience intelligence
Analyze public comments on your videos or competitors to find repeated questions, objections, and demand.
AI agent context
Give Claude, Codex, or your MCP agent structured comments and replies without copy-pasting threads.
Launch monitoring
Watch newest comments after a launch, announcement, or campaign and route emerging concerns quickly.
Content research
Turn repeated viewer questions and requests into the next video, FAQ, tutorial, or product explanation.
Product feedback
Capture objections, setup friction, and feature requests when a video introduces your product.
Competitor research
Study public comment sections to see where competing content leaves an audience unconvinced or unanswered.
Compare approaches
Spend time on the insight, not the collection layer.
| What you need | FetchLayer | Official API | Build it yourself |
|---|---|---|---|
| One URL to structured comments | ✓ | Project setup | You build it |
| No Google Cloud configuration | ✓ | Required | You manage it |
| Nested reply support | ✓ | Multiple methods | You parse it |
| Ready for AI and MCP workflows | ✓ | Your integration | Your integration |
FetchLayer provides access to publicly available data. It is not affiliated with, endorsed by, or sponsored by the platform.
Pricing
Start free. Scale when ready.
Pay per request with no commitment, or lock in a flat monthly rate with built-in savings.
Free plan — 30 requests
Verify responses, inspect the API, no credit card required.
Pay as you go
$1.99
per 1,000 requests
$0.00199 per request · credits never expire
How credits work — no multipliers
One credit = one API call, on every endpoint and platform. No matter how many results come back, you pay for the call, not the output size. Most scraping APIs charge multipliers of 5x, 25x, even 75x per call depending on the target — here it's always 1.
- No multipliers — 1 request = 1 credit
- No monthly commitment
- Credits never expire
- Same API & MCP access as subscribers
- ∞ req/min, ∞ API keys
∞
Expiry
Credits stay until you use them. No monthly reset, no pressure to hit a quota.
0
Commitments
No subscription, no contract, no minimums. Start, pause, or scale whenever.
100%
Access
Every endpoint and MCP included. Not a limited tier — same data as any subscriber.
API reference
Every parameter, documented.
All requests are POST with a JSON body and Bearer auth header.
POST /youtube/comments Extract comments from a YouTube video. Supports sorting by top or newest and pagination through the comment section.
videoUrl* string Full YouTube video URL sort* string 'top' or 'newest'. Default top. limit number Maximum number of top-level comments to return. Defaults to no limit. pages number Number of comment batches to collect. More pages return more comments. Default 1. POST /youtube/comments/replies Extract the replies to a single comment. Returns a comment and its replies.
videoUrl* string YouTube video URL the comment belongs to commentId* string Comment ID returned by the comments endpoint depth number Number of reply levels to include. Defaults to direct replies only. POST /youtube/transcript Extract the transcript from a video as timestamped segments and joined plain text.
videoUrl* string Full YouTube video URL language string Preferred transcript language code, e.g. 'en' or 'en-US'. Defaults to first available track. Fields marked * are required. Full API reference →
FAQ
Common questions.
What can the YouTube Comments API retrieve?
FetchLayer extracts public top-level YouTube comments from a video URL. Each result includes the author username, comment text, likes, relative date, and a hasReplies flag. Use the separate replies endpoint to load a specific comment thread.
Do I need a Google Cloud project or YouTube credentials?
No. Authenticate with your FetchLayer API key and provide the public YouTube video URL you want to retrieve comments from.
Can I retrieve newest comments instead of top comments?
Yes. Set the sort option to top or newest depending on whether you need the most engaged feedback or the latest discussion.
Can an AI agent analyze the comments?
Yes. The endpoint returns structured comment data that you can pass to an LLM or use through FetchLayer’s MCP server to identify sentiment, recurring questions, content ideas, and customer feedback.
Can I analyze and export YouTube comments without code?
Yes. FetchLayer Research Chat can retrieve public comments from a YouTube video, analyze the discussion with AI, and export the structured results as a downloadable CSV or JSON file.
How do I retrieve more comments or replies?
Set a higher pages value to fetch more pages of top-level comments. Use the /comments/replies endpoint with a comment ID to load a specific reply thread with configurable depth.
Can I extract video transcripts?
Yes. The /transcript endpoint returns timestamped segments and joined plain text from any YouTube video, with optional language selection.
Start pulling YouTube comments today.
Get a free API key, make your first request, and put public feedback to work in your own product or research workflow.
Used by developers at
Individual developers or teams — not official partnerships