fetchlayer.dev Sign in Turn YouTube comments into audience insight.
Extract a public video’s comments and replies as structured JSON, then ask focused questions about the feedback. Find what viewers liked, what confused them, what they want next, and where the strongest conversation is happening.
The workflow
Go from scattered feedback to a clear next step.
FetchLayer gives you the public data in a predictable shape. Your code, automation, or AI agent can turn it into an ongoing source of customer insight.
- 01
Fetch the relevant conversation
Provide a public video URL and choose top or newest comments, reply depth, and pages based on the feedback you need.
- 02
Keep comments and replies together
Preserve likes and nested reply context so the analysis can distinguish a popular concern from an isolated observation.
- 03
Ask for an actionable synthesis
Use an LLM or your own analysis to group feedback into themes, cite representative comments, and suggest the next action.
What to surface
Raw feedback becomes useful when it is specific.
Audience reaction
Summarize the tone of the response while retaining the individual comments behind broad sentiment labels.
Repeated questions
Find questions that should become a follow-up video, documentation improvement, or a clearer product explanation.
Content requests
Surface the topics, comparisons, and examples viewers explicitly ask the creator to cover next.
Product feedback
When a video introduces a product, comments become public qualitative feedback about objections, gaps, and value.
Conversation context
Include nested replies where the actual insight comes from the discussion rather than the first comment alone.
Competitor research
Analyze public responses to competitor videos to understand what their audience praises, questions, or rejects.
AI-ready input
Give your agent the raw feedback and a useful question.
Use FetchLayer through REST or MCP. The important part is keeping the original feedback alongside the summary so your team can inspect the evidence behind every conclusion.
Read these YouTube comments and replies. Group the audience feedback into praise, confusion, objections, and requests for future content. Cite the most representative comments for every theme.
Viewers understand the main idea but repeatedly ask for a practical setup tutorial. The strongest objection is uncertainty about pricing; make both themes easy for the creator to inspect in the source comments.
Pricing
Start free. Pay for what you use, or lock in a flat rate.
Credits for flexible, no-commitment usage. Subscriptions for a fixed monthly rate with built-in savings. Subscriptions+ for teams that want volume pricing at scale.
Free plan
30 free requests
A small test drive to verify the API, inspect real responses, and decide whether you want to stay on credits or move to a subscription.
Pay as you go
$1.99 per 1,000 requests
$0.00199 per request
How credits are counted
One credit = one request. No matter how many results come back — replies, comments, search pages — you pay for the call, not the output size.
Your first successful payment unlocks unlimited API keys on the account, including pay-as-you-go credits.
- No monthly commitment — buy only what you need
- Credits never expire — they stay until you use them
- Same API, same MCP access, same data quality
- ∞ req/min
Credits never expire
Buy once, use whenever. There's no monthly reset, no pressure to hit a quota, no wasted credits at the end of a billing cycle.
No strings attached
No subscription to cancel, no seat minimums, no contract to negotiate. Start, pause, or scale whenever you want.
Full access from credit one
Every endpoint, MCP included, is available on credits. You're not on a limited tier — you get the same data as any subscriber.
FAQ
Common questions.
Can FetchLayer analyze YouTube comment sentiment?
FetchLayer retrieves structured public comment data. Send that data to your own model, analytics stack, or MCP-connected agent for sentiment, themes, questions, and qualitative analysis.
Should I analyze top or newest comments?
Use top comments to understand the most visible and engaged feedback. Use newest comments when you need a more current snapshot of how viewers are reacting.
Can I include comment replies in the analysis?
Yes. Set a reply depth to retrieve nested replies when the discussion below a top-level comment is important to the question you are asking.
Start with the public feedback.
Retrieve the source data, keep the evidence, and build the feedback workflow your team actually needs.