Scrape IMDb movie ratings

Extract movie titles, release years, and ratings from IMDb's Top 250 chart.

Prerequisites

• A Browserless API token from your account dashboard

Steps

IMDb's Top 250 page renders with JavaScript and is owned by Amazon, which applies bot-detection measures. The examples below extract the top-rated movies and route through stealth mode with a residential proxy.

Selector stability

IMDb updates its markup periodically. If selectors stop returning results, inspect the live page with browser DevTools to find the current element names.

AI Agent

Use the Browserless MCP server to scrape movie ratings from IMDb from any MCP-compatible AI agent (Claude Desktop, Cursor, Windsurf, ChatGPT, etc.).

1. Connect the MCP server

Send this prompt to your AI agent to install the Browserless MCP server:

Go to https://github.com/browserless/browserless-mcp/blob/main/install.md
and follow the instructions to install the Browserless MCP server
for my client.

2. Scrape IMDb

Use browserless_smartscraper. It handles IMDb's dynamic content and bot protection automatically.

Use the browserless_smartscraper tool to scrape the top 250 movies
from https://www.imdb.com/chart/top/
and return the results as markdown

REST API

Send the BQL mutation over HTTP to the stealth endpoint. No browser library or BQL IDE required.

cURL

View Full Code on GitHub

1. Send the request

curl -X POST \
  "https://production-sfo.browserless.io/stealth/bql?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "mutation ScrapeIMDb { goto(url: \"https://www.imdb.com/chart/top/\", waitUntil: networkIdle) { status } waitForSelector(selector: \".ipc-metadata-list-summary-item\", timeout: 15000) { time } movies: mapSelector(selector: \".ipc-metadata-list-summary-item\") { title: mapSelector(selector: \".ipc-title__text\") { innerText } metadata: mapSelector(selector: \".cli-title-metadata span\") { innerText } rating: mapSelector(selector: \".ipc-rating-star--imdb\") { ratingLabel: attribute(name: \"aria-label\") { value } } } }",
    "variables": {}
  }'

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "waitForSelector": { "time": 2340 },
    "movies": [
      {
        "title": [{ "innerText": "1. The Shawshank Redemption" }],
        "metadata": [{ "innerText": "1994" }, { "innerText": "2h 22m" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.3" } }]
      },
      {
        "title": [{ "innerText": "2. The Godfather" }],
        "metadata": [{ "innerText": "1972" }, { "innerText": "2h 55m" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.2" } }]
      }
    ]
  }
}

JavaScript

View Full Code on GitHub

1. Send the request

const query = `mutation ScrapeIMDb {
  goto(url: "https://www.imdb.com/chart/top/", waitUntil: networkIdle) {
    status
  }
  waitForSelector(selector: ".ipc-metadata-list-summary-item", timeout: 15000) {
    time
  }
  movies: mapSelector(selector: ".ipc-metadata-list-summary-item") {
    title: mapSelector(selector: ".ipc-title__text") { innerText }
    metadata: mapSelector(selector: ".cli-title-metadata span") { innerText }
    rating: mapSelector(selector: ".ipc-rating-star--imdb") {
      ratingLabel: attribute(name: "aria-label") { value }
    }
  }
}`;

const response = await fetch(
  'https://production-sfo.browserless.io/stealth/bql?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us',
  {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ query, variables: {} }),
  }
);

const { data } = await response.json();
console.log(JSON.stringify(data.movies, null, 2));

2. Check the output

[
  {
    "title": [{ "innerText": "1. The Shawshank Redemption" }],
    "metadata": [{ "innerText": "1994" }, { "innerText": "2h 22m" }],
    "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.3" } }]
  },
  {
    "title": [{ "innerText": "2. The Godfather" }],
    "metadata": [{ "innerText": "1972" }, { "innerText": "2h 55m" }],
    "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.2" } }]
  }
]

Python

View Full Code on GitHub

1. Install dependencies

pip install requests

2. Send the request

import requests

query = """
mutation ScrapeIMDb {
  goto(url: "https://www.imdb.com/chart/top/", waitUntil: networkIdle) {
    status
  }
  waitForSelector(selector: ".ipc-metadata-list-summary-item", timeout: 15000) {
    time
  }
  movies: mapSelector(selector: ".ipc-metadata-list-summary-item") {
    title: mapSelector(selector: ".ipc-title__text") { innerText }
    metadata: mapSelector(selector: ".cli-title-metadata span") { innerText }
    rating: mapSelector(selector: ".ipc-rating-star--imdb") {
      ratingLabel: attribute(name: "aria-label") { value }
    }
  }
}
"""

response = requests.post(
    'https://production-sfo.browserless.io/stealth/bql',
    params={
        'token': 'YOUR_API_TOKEN_HERE',
        'proxy': 'residential',
        'proxyCountry': 'us',
    },
    json={'query': query, 'variables': {}},
)

data = response.json()['data']
for movie in data['movies']:
    title = movie['title'][0]['innerText']
    year = movie['metadata'][0]['innerText'] if movie['metadata'] else 'N/A'
    rating = movie['rating'][0]['ratingLabel']['value'] if movie['rating'] else 'N/A'
    print(f'{title} ({year}) - {rating}')

3. Check the output

1. The Shawshank Redemption (1994) - IMDb rating: 9.3
2. The Godfather (1972) - IMDb rating: 9.2

Java

View Full Code on GitHub

1. Send the request

import java.net.URI;
import java.net.http.*;

String token = "YOUR_API_TOKEN_HERE";
String endpoint = "https://production-sfo.browserless.io/stealth/bql?token=" + token
    + "&proxy=residential&proxyCountry=us";

String query = "mutation ScrapeIMDb {"
    + " goto(url: \\\"https://www.imdb.com/chart/top/\\\", waitUntil: networkIdle) { status }"
    + " waitForSelector(selector: \\\".ipc-metadata-list-summary-item\\\", timeout: 15000) { time }"
    + " movies: mapSelector(selector: \\\".ipc-metadata-list-summary-item\\\") {"
    + "   title: mapSelector(selector: \\\".ipc-title__text\\\") { innerText }"
    + "   metadata: mapSelector(selector: \\\".cli-title-metadata span\\\") { innerText }"
    + "   rating: mapSelector(selector: \\\".ipc-rating-star--imdb\\\") { ratingLabel: attribute(name: \\\"aria-label\\\") { value } }"
    + " }"
    + " }";

String payload = "{\"query\": \"" + query + "\", \"variables\": {}}";

HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create(endpoint))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString(payload))
    .build();

HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "waitForSelector": { "time": 2340 },
    "movies": [
      {
        "title": [{ "innerText": "1. The Shawshank Redemption" }],
        "metadata": [{ "innerText": "1994" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.3" } }]
      }
    ]
  }
}

C#

View Full Code on GitHub

1. Send the request

using System.Net.Http;
using System.Text;
using System.Text.Json;

string token = "YOUR_API_TOKEN_HERE";
string endpoint = $"https://production-sfo.browserless.io/stealth/bql?token={token}&proxy=residential&proxyCountry=us";

var payload = new
{
    query = @"mutation ScrapeIMDb {
      goto(url: ""https://www.imdb.com/chart/top/"", waitUntil: networkIdle) { status }
      waitForSelector(selector: "".ipc-metadata-list-summary-item"", timeout: 15000) { time }
      movies: mapSelector(selector: "".ipc-metadata-list-summary-item"") {
        title: mapSelector(selector: "".ipc-title__text"") { innerText }
        metadata: mapSelector(selector: "".cli-title-metadata span"") { innerText }
        rating: mapSelector(selector: "".ipc-rating-star--imdb"") {
          ratingLabel: attribute(name: ""aria-label"") { value }
        }
      }
    }",
    variables = new { },
};

using (HttpClient httpClient = new HttpClient())
{
    var content = new StringContent(
        JsonSerializer.Serialize(payload), Encoding.UTF8, "application/json");
    var response = await httpClient.PostAsync(endpoint, content);
    string body = await response.Content.ReadAsStringAsync();
    Console.WriteLine(body);
}

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "waitForSelector": { "time": 2340 },
    "movies": [
      {
        "title": [{ "innerText": "1. The Shawshank Redemption" }],
        "metadata": [{ "innerText": "1994" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.3" } }]
      }
    ]
  }
}

Frameworks

Connect through stealth mode and a residential proxy so IMDb sees traffic from a real browser, then extract movie data from the rendered chart.

Puppeteer

View Full Code on GitHub

1. Install dependencies

npm install puppeteer-core

2. Connect and scrape

import puppeteer from 'puppeteer-core';

const browser = await puppeteer.connect({
  browserWSEndpoint:
    'wss://production-sfo.browserless.io/stealth?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us',
});

try {
  const page = await browser.newPage();
  await page.goto('https://www.imdb.com/chart/top/', {
    waitUntil: 'networkidle2',
  });

  await page.waitForSelector('.ipc-metadata-list-summary-item');

  const movies = await page.evaluate(() =>
    Array.from(document.querySelectorAll('.ipc-metadata-list-summary-item')).map((item) => ({
      title: item.querySelector('.ipc-title__text')?.innerText?.trim() ?? '',
      year: item.querySelector('.cli-title-metadata span')?.innerText?.trim() ?? '',
      rating: item.querySelector('.ipc-rating-star--imdb')?.getAttribute('aria-label') ?? '',
    }))
  );

  console.log(JSON.stringify(movies.slice(0, 10), null, 2));
} finally {
  await browser.close();
}

3. Check the output

Run with node scrape-imdb.mjs. Each object has title, year, and rating fields.

[
  {
    "title": "1. The Shawshank Redemption",
    "year": "1994",
    "rating": "IMDb rating: 9.3"
  },
  {
    "title": "2. The Godfather",
    "year": "1972",
    "rating": "IMDb rating: 9.2"
  }
]

Playwright

View Full Code on GitHub

1. Install dependencies

npm install playwright-core

2. Connect and scrape

import { chromium } from 'playwright-core';

const browser = await chromium.connectOverCDP(
  'wss://production-sfo.browserless.io?token=YOUR_API_TOKEN_HERE&stealth&proxy=residential&proxyCountry=us'
);

try {
  const context = browser.contexts()[0];
  const page = await context.newPage();
  await page.goto('https://www.imdb.com/chart/top/', {
    waitUntil: 'networkidle',
  });

  await page.waitForSelector('.ipc-metadata-list-summary-item');

  const movies = await page.evaluate(() =>
    Array.from(document.querySelectorAll('.ipc-metadata-list-summary-item')).map((item) => ({
      title: item.querySelector('.ipc-title__text')?.innerText?.trim() ?? '',
      year: item.querySelector('.cli-title-metadata span')?.innerText?.trim() ?? '',
      rating: item.querySelector('.ipc-rating-star--imdb')?.getAttribute('aria-label') ?? '',
    }))
  );

  console.log(JSON.stringify(movies.slice(0, 10), null, 2));
} finally {
  await browser.close();
}

3. Check the output

Run with node scrape-imdb.mjs. Each object has title, year, and rating fields.

[
  {
    "title": "1. The Shawshank Redemption",
    "year": "1994",
    "rating": "IMDb rating: 9.3"
  },
  {
    "title": "2. The Godfather",
    "year": "1972",
    "rating": "IMDb rating: 9.2"
  }
]

BQL

View Full Code on GitHub

1. Write the mutation

Navigate to IMDb's Top 250 chart, wait for the list to render, then extract movie titles, years, and ratings. We use /stealth/bql because IMDb (Amazon-owned) applies bot detection that blocks standard headless browsers.

mutation ScrapeIMDb {
  goto(url: "https://www.imdb.com/chart/top/", waitUntil: networkIdle) {
    status
  }
  waitForSelector(selector: ".ipc-metadata-list-summary-item", timeout: 15000) {
    time
  }
  movies: mapSelector(selector: ".ipc-metadata-list-summary-item") {
    title: mapSelector(selector: ".ipc-title__text") { innerText }
    metadata: mapSelector(selector: ".cli-title-metadata span") { innerText }
    rating: mapSelector(selector: ".ipc-rating-star--imdb") {
      ratingLabel: attribute(name: "aria-label") { value }
    }
  }
}

2. Run it

Paste into the BQL IDE and click Run.

3. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "waitForSelector": { "time": 2340 },
    "movies": [
      {
        "title": [{ "innerText": "1. The Shawshank Redemption" }],
        "metadata": [{ "innerText": "1994" }, { "innerText": "2h 22m" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.3" } }]
      },
      {
        "title": [{ "innerText": "2. The Godfather" }],
        "metadata": [{ "innerText": "1972" }, { "innerText": "2h 55m" }],
        "rating": [{ "ratingLabel": { "value": "IMDb rating: 9.2" } }]
      }
    ]
  }
}

Next steps

• Scrape GitHub Trending Repos -- scrape trending repositories from GitHub
• Scrape Amazon Product Listings -- scrape another Amazon-owned property with stealth mode
• Scrape Structured Data -- extract data from other sites using the /scrape endpoint