Extract public Rotten Tomatoes movie and TV metadata, Tomatometer scores, audience scores, critic reviews, and audience reviews from Rotten Tomatoes URLs.
Use this actor when you need structured review intelligence for media research, entertainment marketing, reputation monitoring, content planning, or internal analytics.
What does Rotten Tomatoes Movies & Reviews Scraper do?
This actor turns public Rotten Tomatoes title pages and review pages into clean dataset rows.
It can collect:
- 🍅 Title metadata
- 🍅 Tomatometer scores
- 🍿 Audience scores
- 📝 Critic review excerpts
- 🧑 Audience review excerpts
- 🏆 Top critic flags
- ✅ Verified audience flags
- 🔗 Review source URLs
Each run starts from the Rotten Tomatoes URLs you provide.
The actor saves one metadata row for each title and then saves review rows for the selected review types.
Who is it for?
Media analysts
Track critic and audience reactions across movies and shows.
Entertainment marketers
Monitor public review excerpts, score changes, and audience sentiment signals.
SEO and content teams
Build comparison pages, review roundups, title pages, and market snapshots from structured data.
Data teams
Feed normalized movie review data into dashboards, warehouses, BI tools, or internal enrichment pipelines.
Reputation monitors
Watch how a title is being described by publications and public audiences.
Why use this actor?
Rotten Tomatoes is a high-signal public source for entertainment reputation.
Manual copying is slow, inconsistent, and hard to repeat.
This actor gives you repeatable extraction with clear columns, pagination support, and both title-level and review-level context.
What data can you extract?
| Field group | Examples |
|---|---|
| Title identity | mediaTitle, media URL, media type, Rotten Tomatoes vanity path |
| Release metadata | release date, release year, content rating, runtime |
| Creative metadata | genres, directors, cast when visible |
| Scores | Tomatometer score, audience score, review counts, average ratings |
| Critic reviews | critic name, publication, top critic flag, quote, sentiment, review URL |
| Audience reviews | display name, verified flag, star rating, review text, date |
| Traceability | input URL, source endpoint, pagination cursor, scraped timestamp |
How to use it
- Open the actor on Apify.
- Add one or more Rotten Tomatoes movie, TV, or review URLs.
- Choose the review types you want.
- Set the maximum number of reviews per title and type.
- Run the actor.
- Export the dataset as JSON, CSV, Excel, XML, or RSS.
Supported URLs
You can provide URLs such as:
https://www.rottentomatoes.com/m/toy_story
https://www.rottentomatoes.com/m/toy_story/reviews
https://www.rottentomatoes.com/m/toy_story/reviews?type=user
Review URLs are normalized back to their title page so the actor can collect both title context and review data.
Example input
{
"startUrls": [
{ "url": "https://www.rottentomatoes.com/m/toy_story" }
],
"reviewTypes": ["critic", "audience"],
"includeAudienceReviews": true,
"maxReviewsPerTitle": 25,
"proxyConfiguration": { "useApifyProxy": false }
}
Example output
{
"mediaTitle": "Toy Story",
"reviewType": "critic",
"tomatometerScore": 100,
"audienceScore": 92,
"reviewerName": "Sarah Vincent",
"publicationName": "Sarah G Vincent Views",
"reviewSentiment": "POSITIVE",
"reviewQuote": "Toy Story is a midlife crisis...",
"reviewDate": "2026-06-19T10:51:07.000Z",
"mediaUrl": "https://www.rottentomatoes.com/m/toy_story"
}
Tips for best results
Start with one URL and a low review limit.
Use multiple URLs only after confirming that the output matches your workflow.
Choose only the review types you need.
Audience reviews can be numerous, so increase limits gradually.
Export JSON when sending data to another system.
Export CSV or Excel for spreadsheets.
Integrations
You can connect the dataset to:
- Google Sheets for editorial tracking
- BigQuery or Snowflake for analytics
- Airtable for research queues
- Slack alerts for monitored titles
- Zapier or Make workflows for no-code automation
- Internal dashboards for movie and TV score monitoring
API usage with Node.js
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/rotten-tomatoes-movies-reviews-scraper').call({
startUrls: [{ url: 'https://www.rottentomatoes.com/m/toy_story' }],
reviewTypes: ['critic', 'audience'],
maxReviewsPerTitle: 25
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
API usage with Python
from apify_client import ApifyClient
client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('fetch_cat/rotten-tomatoes-movies-reviews-scraper').call(run_input={
'startUrls': [{'url': 'https://www.rottentomatoes.com/m/toy_story'}],
'reviewTypes': ['critic', 'audience'],
'maxReviewsPerTitle': 25,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)
API usage with cURL
curl -X POST "https://api.apify.com/v2/acts/fetch_cat~rotten-tomatoes-movies-reviews-scraper/runs?token=$APIFY_TOKEN" \
-H 'Content-Type: application/json' \
-d '{
"startUrls": [{"url": "https://www.rottentomatoes.com/m/toy_story"}],
"reviewTypes": ["critic", "audience"],
"maxReviewsPerTitle": 20
}'
MCP integration
Use this actor through Apify MCP when working in Claude Code, Claude Desktop, or other MCP-compatible tools.
MCP server URL:
https://mcp.apify.com/?tools=fetch_cat/rotten-tomatoes-movies-reviews-scraper
Claude Code setup:
claude mcp add apify https://mcp.apify.com/?tools=fetch_cat/rotten-tomatoes-movies-reviews-scraper
Claude Desktop or other MCP client configuration:
{
"mcpServers": {
"apify-rotten-tomatoes": {
"url": "https://mcp.apify.com/?tools=fetch_cat/rotten-tomatoes-movies-reviews-scraper"
}
}
}
Example prompts:
- "Scrape critic reviews for this Rotten Tomatoes URL and summarize recurring praise."
- "Collect audience reviews for these three titles and compare sentiment."
- "Create a table of Tomatometer and audience scores for my movie list."
Common workflows
Track a release
Run the actor daily for the same title and compare new review rows over time.
Build critic quote collections
Collect critic review excerpts and filter by publication, date, or sentiment.
Compare critic and audience reaction
Select both critic and audience reviews, then group by reviewType.
Enrich a movie database
Use title metadata and score fields to enrich internal movie or TV records.
Troubleshooting
The actor saved metadata but no reviews
The title page may not expose the public review identifier needed for pagination, or the selected review type may have no public rows.
Try a lower limit and a well-known public title first.
I requested top critic or verified audience reviews and received fewer rows
Those modes filter the public critic or audience stream. If few rows match the flag, the output can be smaller than the limit.
Some fields are empty
Rotten Tomatoes does not expose every field for every title or review. Empty values are returned as null or empty arrays.
Legality and responsible use
This actor extracts publicly available information from Rotten Tomatoes pages and public review data.
You are responsible for using the data in a lawful way and respecting applicable terms, privacy rules, and intellectual property rights.
Do not use the actor to collect private account data or bypass access controls.
Limits
The actor is designed for public title and review pages.
It does not log in.
It does not collect private user profile data.
It does not guarantee that every historical review is available from public pages.
Support
If you need help, open an issue from the actor page on Apify and include your run ID plus a short description of the expected output.
