YouTube Live Chat Replay Scraper - Ended Streams

Export the full chat replay of ended YouTube livestreams & premieres: messages, Super Chats, memberships. No API key. The official API cannot do this.

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What does the YouTube Live Chat Replay Scraper do?

This Actor turns YouTube Live Chat Replay into a structured dataset you can actually work with. You give it a search, it walks the result pages, and it writes one clean row per record into your dataset — ready to export as JSON, CSV or Excel, or to pull straight from the Apify API.

It runs on plain HTTP with no browser and no login, which keeps it fast and cheap, and it works the same on a free account as on a paid one. Every field documented below came from a real verification run of this Actor, so what you read here is what you get.

The current build returns 11 populated fields per record, of which 10 are present on virtually every row.

Who is it for?

• Analysts who need YouTube Live Chat Replay data as a spreadsheet instead of a browser tab.
• Operations and research teams tracking how YouTube Live Chat Replay listings change over time.
• Developers wiring a live data feed into an internal tool or database.
• Growth and sales teams building prospect and market lists from public data.
• AI teams assembling structured training or grounding data.

Use cases

• Export a full YouTube Live Chat Replay search into a spreadsheet for analysis.
• Track how prices, volumes or availability move week over week by scheduling the run.
• Feed a dashboard or internal database with a repeatable, structured source.
• Build a market map by running several searches in one job.
• Enrich an existing list by matching on the identifiers in the output.

Why use this YouTube Live Chat Replay Scraper?

• 🔑 No API key and no login — nothing to authenticate, nothing to expire.
• 📦 11 verified fields — every column below was confirmed against live output.
• 📄 Real pagination — it walks the result set instead of returning the first screen.
• 🎯 Bounded runs — caps in the input stop the job exactly where you want, so the bill is predictable.
• 💸 Tiered pay-per-result — you pay per row, and higher Apify plans pay less per row.
• 📊 Export anywhere — JSON, CSV, Excel, HTML, the API, or any Apify integration.

What data can you extract?

One row per record. These columns come from a live run, with the share of rows that carried a value:

Field	Type	Typically filled	Description
authorChannelId	string	100%	Author channel id
authorName	string	100%	Author name
message	string	100%	Message
messageId	string	100%	Message id
source	string	100%	Source
timestampText	string	100%	Timestamp text
timestampUsec	string	100%	Timestamp usec
type	string	100%	Type
videoId	string	100%	Video id
videoOffsetTimeMsec	string	100%	Video offset time msec
authorBadges	string	5%	Author badges

Fields below 90% are genuinely optional at the source — YouTube Live Chat Replay does not publish them for every record. An empty value means the source did not show it, not that extraction failed.

How to use

1. Open the Actor and fill in the search fields — the defaults below are a working example.
2. Set the result cap so the run stops where you want it.
3. Click Start, then export from the Output tab or pull the dataset through the API.

{
  "videoUrls": [
    "https://www.youtube.com/watch?v=_USAoRuPdl4"
  ],
  "includeNormalMessages": true,
  "includeSuperChats": true,
  "includeMemberships": true,
  "maxMessagesPerVideo": 0,
  "maxItems": 1000,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

Input parameters

Parameter	Type	Default	Description
videoUrls	array	–	YouTube video URLs of ENDED livestreams or premieres that have chat replay.
videoIds	array	[]	Alternatively, 11-character YouTube video IDs.
includeNormalMessages	boolean	true	Include regular text chat messages.
includeSuperChats	boolean	true	Include paid Super Chats and Super Stickers (with the amount paid).
includeMemberships	boolean	true	Include channel membership / gift events.
maxMessagesPerVideo	integer	0	Cap per video.
maxItems	integer	0	Hard cap on total chat items across all videos.
proxyConfiguration	object	{"useApifyProxy": true}	Proxy settings.

Tips for best results

• Broad searches return the deepest result sets; very narrow ones run out after a page or two.
• Use the result cap rather than the page cap when you want a predictable bill.
• Schedule the same input daily or weekly to build a history instead of a one-off snapshot.
• Lower the concurrency if you see retries — the source rate-limits aggressive crawling.
• Run several searches in one job instead of one search with a huge page count.
• Empty optional fields are normal; filter on the columns that matter to you after export.
• Deduplicate on the identifier column if you merge several runs together.
• Keep the proxy setting on the default unless the source blocks your region.

Integrations

Push results straight into Google Sheets, Slack, Zapier, Make, Airtable or any Webhook. You can also schedule the Actor and have each run append to the same dataset, which is how you turn a single export into a time series.

API usage

Replace <YOUR_TOKEN> with your Apify API token.

cURL

curl -X POST "https://api.apify.com/v2/acts/logiover~youtube-live-chat-replay-scraper/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"videoUrls": ["https://www.youtube.com/watch?v=_USAoRuPdl4"], "includeNormalMessages": true, "includeSuperChats": true, "includeMemberships": true, "maxMessagesPerVideo": 0, "maxItems": 1000, "proxyConfiguration": {"useApifyProxy": true}}'

Python

from apify_client import ApifyClient

client = ApifyClient('<YOUR_TOKEN>')
run = client.actor('logiover/youtube-live-chat-replay-scraper').call(run_input={"videoUrls": ["https://www.youtube.com/watch?v=_USAoRuPdl4"], "includeNormalMessages": true, "includeSuperChats": true, "includeMemberships": true, "maxMessagesPerVideo": 0, "maxItems": 1000, "proxyConfiguration": {"useApifyProxy": true}})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_TOKEN>' });
const run = await client.actor('logiover/youtube-live-chat-replay-scraper').call({"videoUrls": ["https://www.youtube.com/watch?v=_USAoRuPdl4"], "includeNormalMessages": true, "includeSuperChats": true, "includeMemberships": true, "maxMessagesPerVideo": 0, "maxItems": 1000, "proxyConfiguration": {"useApifyProxy": true}});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

🤖 AI Agents, MCP & RAG Integration

This Actor is reachable through the Apify MCP server, so an AI agent can call it as a tool. Point the agent at https://mcp.apify.com and ask it something like "pull the first 200 results from YouTube Live Chat Replay and summarise them" — it receives the same structured rows you would get from the UI.

Connect this Actor directly to Apify AI, Claude Desktop, Cursor, VS Code, Windsurf, LangChain, or LlamaIndex via the official Apify MCP Server — no custom wrapper code needed:

{
  "mcpServers": {
    "apify": {
      "type": "http",
      "url": "https://mcp.apify.com?tools=logiover/youtube-live-chat-replay-scraper"
    }
  }
}

• Schema-typed inputs & outputs: Clean JSON records with explicit .actor/input_schema.json and .actor/output_schema.json definitions so LLM agents infer parameters and parse fields accurately without HTML noise.
• Bounded & predictable runs: Built-in volume caps and pay-per-result budget guards prevent runaway agent tool loops.
• RAG & automation ready: Stream run datasets straight into vector stores, n8n, Make, Zapier, or webhook pipelines.

FAQ

Do I need a YouTube Live Chat Replay account or API key?

No. The Actor reads publicly available pages only. There is nothing to authenticate and no credentials to rotate.

Does it work on the free plan?

Yes. Every feature is available on a free Apify account — nothing is gated behind a paid tier. Pricing is per result, and higher plans simply pay less per row.

How many results can I get in one run?

As many as the search exposes. Raise the page and result caps together; the run stops at whichever limit it reaches first.

Why did I get fewer rows than I asked for?

The search ran out of records. That is normal for narrow queries — broaden the search or add more searches to one run.

Why are some fields empty?

YouTube Live Chat Replay does not publish every attribute for every record. The table above shows how often each field is filled in practice.

What export formats are supported?

JSON, CSV, Excel, HTML and RSS from the Output tab, plus the Apify API and any integration you connect.

How fast is it?

It is pure HTTP with no browser, so a page of results typically takes a second or two.

Can I schedule it?

Yes. Use the Apify scheduler to run it on any interval and append each run to the same dataset.

Does it use a proxy?

It routes through Apify Proxy by default. You can switch groups or supply your own proxies in the input.

Is the output schema stable?

Yes. Field names and types are fixed, so downstream pipelines will not break between runs.

How often is the data refreshed?

Every run reads the live source. There is no cache, so the data is as current as the website itself.

What if the site changes its layout?

Open an issue on the Issues tab and it gets fixed — the Actor is actively maintained.

💬 Support, Issues & Reviews

• Bug reports & target-site changes: Hit an unexpected empty result or selector change? Open a ticket in the Issues tab with your Run ID or sample input — we actively monitor issues and ship fixes fast.
• Feature & field requests: Need an additional data attribute or filter? Request it in the Issues tab.
• Enjoying this Actor? If it saved you engineering time, please consider leaving an honest review on Apify Store or bookmarking logiover/youtube-live-chat-replay-scraper — organic developer feedback helps others discover reliable tools and keeps maintenance prioritized.

Is it legal?

This Actor reads only publicly available pages on YouTube Live Chat Replay — the same content any visitor sees without logging in. It does not bypass authentication and does not collect private data. You remain responsible for how you use the output: respect the source's terms of service, applicable copyright, and data-protection law such as GDPR where personal data is involved.

This Actor is an independent tool. It is not affiliated with, endorsed by, or sponsored by YouTube Live Chat Replay; YouTube Live Chat Replay and all other trademarks mentioned here are the property of their respective owners.

Output example

One row from a real run of this Actor:

{
  "videoId": "_USAoRuPdl4",
  "messageId": "ChwKGkNLREdsdG0wdFpVREZVZ2JkZ1lkdEVJVUh3",
  "type": "message",
  "authorName": "@_aninhaa77",
  "authorChannelId": "UCgjdA7Q8TFVB7S7Y0EM4GQA",
  "authorBadges": [
    "Moderator"
  ],
  "message": "hi guys, welcome!",
  "superChatAmount": null,
  "timestampUsec": "1783044048791336",
  "timestampText": "0:42",
  "videoOffsetTimeMsec": "42076",
  "source": "youtube-live-chat-replay"
}

Related scrapers

Other Actors from the same collection:

• YouTube Search
• YouTube Comments
• YouTube Channel
• YouTube Channel Email

📝 Changelog

2026-11-11

• Added reliable terminal run status telemetry and structured Apify AI / MCP Server (mcp.apify.com) tool configuration.
• Added direct Issues & Reviews support links and refreshed live maintenance verification.

2026-11-01

• Monthly health check (2026-11-01): a live run on the current build completed successfully and returned data. Input options, output fields and pricing are unchanged.
• README refreshed: independence disclaimer added.
• README refreshed: duplicate "Related scrapers" sections merged.

2026-10-15

• Every request now has a hard time limit, so a proxy connection that stalls can no longer hold up the run or push it past its timeout.
• A run that reaches its maximum cost per run now stops cleanly with its results saved and a status message, instead of ending as aborted.
• A proxy group your account cannot use no longer stops the run at start-up; it falls back to the default Apify Proxy.
• Memory is managed within the run's own limit, which removes a rare out-of-memory crash on large pages.
• The prefilled example for maxItems is now 333 (was 1,000).
• The default used when the field is left out for maxItems is now 6,666 (was 0).

2026-09-23

• Fleet-wide quality audit. Verified end to end against live data and re-checked the input schema, the output columns and the run configuration.
• Output verified on a live run: 12 columns returned, 83.8% of cells populated.
• Run reliability reviewed: 100.0% of public runs succeeded in the last 30 days.
• Input schema, output schema and pricing configuration reviewed.
• Noted that 1 column(s) came back empty in this sample (superChatAmount); these are under review.

2026-09-01

• Fleet-wide health check. Verified against this Actor's real run history: 30-day success rate, output row counts, per-field fill rates, and peak memory against the configured memory limit.
• Reviewed for the failure patterns that have cost this fleet runs — unguarded proxy setup, retry loops that can outlast the run's own time budget, and full-page HTML parsing that can exhaust a small container.
• No change to input, output fields or scraping logic.

2026-08-11

• Maintenance release: refreshed the build and dependencies.
• Re-verified live execution, non-empty structured output and dataset field/type integrity.
• Reviewed reliability (retries, pagination) and output quality as part of a full-fleet QA pass.

2026-08-01

• Completed the August 2026 full health check: verified empty/programmatic default, Console UI default, and two source-informed alternative inputs on Apify.
• Confirmed successful live execution, non-empty structured output, dataset-field/type integrity, and logical sample quality within the 5-minute quality window.
• Added a working, 1,000-item-bounded default chat replay for empty-input runs.
• Fixed per-video caps so a replay batch cannot overshoot maxMessagesPerVideo, and corrected filtered replay traversal so normal-only pages do not prematurely stop paid or membership searches.
• Declared 12 dataset fields from typed live cloud samples so the output contract is no longer an empty placeholder.
• Declared 12 nullable dataset fields from typed live cloud samples so the output contract is no longer an empty placeholder or brittle to sparse modes.