# IMDb Reviews Scraper (`omkar-cloud/imdb-reviews-scraper`) Actor

Scrape IMDb user reviews by title URL or movie/show name — review title, full text, author rating out of 10, date, helpful votes & spoiler flags. Sort by helpfulness, newest, or rating; filter out spoilers. $1 per 1,000 reviews — 5× cheaper than alternatives, no start fee.

- **URL**: https://apify.com/omkar-cloud/imdb-reviews-scraper.md
- **Developed by:** [Chetan Jain](https://apify.com/omkar-cloud) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## IMDb Reviews Scraper — Extract Movie & TV Show User Reviews

Scrape IMDb user reviews for any movie or TV show — full review text, author ratings, dates, helpful votes, and spoiler flags. No coding required.

Paste IMDb title URLs (or just type movie/show names), click Start, and get one clean JSON record per review: review title, **full text**, the author's rating out of 10, author nickname and profile ID, submission date, **helpful up/down votes**, and the spoiler flag. Sort by **helpfulness, newest, oldest, rating, or votes**, and optionally **filter out spoiler reviews** server-side — filtered reviews are never billed.

Titles can be given as any `imdb.com/title/tt…` URL, or simply by name — "Breaking Bad" resolves to the right title automatically via IMDb search (never billed). Raise **Max Titles per Name** to scrape a whole franchise's reviews from one query.

All this at **$1 per 1,000 reviews** — 5× cheaper than comparable scrapers, with **no start fee** and no monthly rental.

**Rated Excellent — 4.6 based on 25 reviews** on [Trustpilot](https://www.trustpilot.com/review/omkar.cloud).

### Output example: IMDb review data in JSON

Each review becomes one dataset item:

```json
{
  "title_id": "tt4154796",
  "title_name": "Avengers: Endgame",
  "title_url": "https://www.imdb.com/title/tt4154796/",
  "query": "Avengers Endgame",
  "id": "rw11203827",
  "title": "It's Been a Long, Long Time",
  "text": "This was the conclusion of a 10-year story, and they did such a great job during the last hour of the movie that one can almost forget about some of the aspects of the movie that just don't make sense...",
  "rating": 8,
  "author": { "id": "ur96346298", "nickname": "sangomiguel" },
  "date": "2026-02-11",
  "is_spoiler": true,
  "helpful_votes": { "up": 15, "down": 2 }
}
```

You can download the dataset as JSON, CSV, Excel, XML, or an HTML table.

### What data does the IMDb Reviews Scraper extract?

| Data group | Fields |
|------------|--------|
| Review | Review title, full text, author rating out of 10, submission date, review ID |
| Author | Nickname and IMDb profile ID |
| Engagement | Helpful votes up and down, spoiler flag |
| Title context | Title tt-id, name, IMDb link, and your original `query` — every row is self-contained |

### How to scrape IMDb reviews

1. Click **Try for free**.
2. Paste **IMDb title URLs** and/or type **movie or show names** — names resolve to titles automatically.
3. Pick a **sort order** (most helpful by default), set **Max Reviews per Title**, and optionally exclude spoilers.
4. Click **Start** and wait for the run to finish.
5. Open the **Dataset** tab to preview your data, then download it as **JSON, CSV, Excel, XML, or an HTML table**.

No proxies, no browser setup, no CAPTCHA solving.

### Input

```json
{
  "startUrls": ["https://www.imdb.com/title/tt4154796/"],
  "searchQueries": ["Breaking Bad"],
  "maxTitlesPerSearch": 1,
  "maxReviewsPerTitle": 100,
  "sortBy": "helpfulness",
  "includeSpoilers": true,
  "country": "US"
}
```

| Field | Type | Description |
|-------|------|-------------|
| `startUrls` | array | IMDb title page URLs (any `imdb.com/title/tt…` URL, review pages included). |
| `searchQueries` | array | Movie/show names — each resolves via IMDb search to its top match(es), never billed. |
| `maxTitlesPerSearch` | integer | Search matches to scrape per name (default 1). |
| `maxReviewsPerTitle` | integer | Max reviews per title (default 100, 25 per page). Controls your cost. |
| `sortBy` | string | `helpfulness` (default), `newest`, `oldest`, `rating`, `votes`. |
| `includeSpoilers` | boolean | Off = spoiler-flagged reviews are skipped server-side and never billed. |
| `country` | string | 2-letter code localizing regional title names (default `US`). |

### How much does it cost to scrape IMDb reviews?

Scraping IMDb reviews costs **$1 per 1,000 reviews** ($0.001 per review) — 5× cheaper than comparable scrapers (which charge ~$5 per 1,000 plus up to a $0.09 fee every run), with **no Actor start fee**. Title discovery is free: searches and URL resolution are never billed.

Apify gives you **$5 in free credits** every month, so you can scrape your first **5,000 reviews** free and test the IMDb Reviews Scraper before paying anything.

### FAQs

#### Why scrape IMDb reviews?

- **Sentiment analysis** — thousands of dated, rated review texts per title, ready for NLP.
- **Audience research** — see what viewers praise and criticize, sorted by helpfulness so the most representative opinions come first.
- **Reception tracking** — scrape newest-first on a schedule to follow how opinion shifts after release.
- **Datasets for ML** — clean JSON with ratings, votes, and spoiler labels.

#### Can I scrape reviews for several titles in one run?

Yes — add as many URLs and names as you like. Every row carries the title's id, name, and link plus your original `query`, so one dataset with many titles stays easy to split.

#### Will I be charged twice if the same title appears twice?

No. Titles are deduplicated per run — the same title arriving via a URL and a name search is scraped once. Every review row is billed exactly once, filtered-out spoiler reviews are never billed, and failed pages are never billed.

#### How many reviews can I get per title?

As many as IMDb serves — popular titles have thousands (Avengers: Endgame has ~10,000). Set **Max Reviews per Title** to cap the spend per title.

#### Is it legal to scrape IMDb reviews?

The Actor extracts publicly available reviews only — visible to any visitor, no login involved. Author nicknames are public by the reviewer's choice. You are responsible for how you use the data; consult a lawyer if unsure about your use case.

#### Need title data too?

Use our **[IMDb Scraper](https://apify.com/omkar-cloud/imdb-scraper)** — search 11M+ titles with filters, scrape the Top 250 and box-office charts, and pull full title profiles with cast and box office, from $1 per 1,000 titles.

### Support

Built by developers, for developers — when you reach out, you talk to the engineers who built the Actor, not a support script. Message us anytime and we'll resolve your query within 1 working day.

[![Contact Us on WhatsApp about IMDb Reviews Scraper](https://raw.githubusercontent.com/omkarcloud/assets/master/images/whatsapp-us.png)](https://api.whatsapp.com/send?phone=918178804274\&text=I%20have%20a%20question%20about%20the%20IMDb%20Reviews%20Scraper.)

Email: [happy.to.help@omkar.cloud](mailto:happy.to.help@omkar.cloud?subject=IMDb%20Reviews%20Scraper%20Question)

[![Email Us about IMDb Reviews Scraper](https://raw.githubusercontent.com/omkarcloud/assets/master/images/ask-on-email.png)](mailto:happy.to.help@omkar.cloud?subject=IMDb%20Reviews%20Scraper%20Question)

### Love It? Star It! ⭐

From one business owner to another: if this Actor saved you hours of copying reviews off IMDb, please [rate the IMDb Reviews Scraper on Apify](https://apify.com/omkar-cloud/imdb-reviews-scraper/reviews).

Here's why it matters: most people judge an Actor by its reviews before trying it. Your rating helps the next person hit "Try for free" with confidence, and it helps the Actor rank higher in the Apify Store.

It takes only 1 second, and means the world to me.

# Actor input Schema

## `startUrls` (type: `array`):

Title page URLs to scrape reviews from. Titles are deduplicated per run.

## `searchQueries` (type: `array`):

Movie/show names to search. Each name resolves to its top-matching title(s); rows carry a `query` field so you can tell them apart.

## `maxTitlesPerSearch` (type: `integer`):

How many search matches to scrape per name (default 1 — the top match). Raise it to scrape reviews of a whole franchise from one query.

## `maxReviewsPerTitle` (type: `integer`):

Maximum number of reviews to scrape per title (25 per page). Use this to control your cost (1,000 reviews ≈ $1).

## `sortBy` (type: `string`):

Order in which reviews are scraped.

## `includeSpoilers` (type: `boolean`):

Off = reviews flagged as spoilers are skipped (and never billed). Each row carries an `is_spoiler` flag either way.

## `country` (type: `string`):

2-letter country code that localizes regional title names (US, GB, DE, IN, …).

## Actor input object example

```json
{
  "startUrls": [
    "https://www.imdb.com/title/tt4154796/"
  ],
  "searchQueries": [
    "Avengers Endgame",
    "Breaking Bad"
  ],
  "maxTitlesPerSearch": 1,
  "maxReviewsPerTitle": 100,
  "sortBy": "helpfulness",
  "includeSpoilers": true,
  "country": "US"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startUrls": [
        "https://www.imdb.com/title/tt4154796/"
    ],
    "maxReviewsPerTitle": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("omkar-cloud/imdb-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "startUrls": ["https://www.imdb.com/title/tt4154796/"],
    "maxReviewsPerTitle": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("omkar-cloud/imdb-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "startUrls": [
    "https://www.imdb.com/title/tt4154796/"
  ],
  "maxReviewsPerTitle": 100
}' |
apify call omkar-cloud/imdb-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,omkar-cloud/imdb-reviews-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/LbIhPBp29QccDRaXM/builds/xv8f2kZ6w9D7uUdBI/openapi.json