# Goodreads Books & Reviews Scraper (`fetch_cat/goodreads-books-reviews-scraper`) Actor

Extract public Goodreads book metadata, ratings, and reader reviews from book URLs or search queries for research and book marketing workflows.

- **URL**: https://apify.com/fetch\_cat/goodreads-books-reviews-scraper.md
- **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community)
- **Categories:** Marketing, E-commerce, Automation
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.60 / 1,000 book or review items

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

## Goodreads Books & Reviews Scraper

Extract public Goodreads book metadata, aggregate ratings, and reader reviews from Goodreads book URLs or search queries.

### What does Goodreads Books & Reviews Scraper do?

Goodreads Books & Reviews Scraper collects structured data from public Goodreads book pages.

It can save book metadata rows and public review rows in the same dataset.

Use it when you need book-market signals without manually copying Goodreads pages.

### Who is it for?

📚 Publishers can monitor reader reaction to backlist and frontlist titles.

✍️ Authors can analyze public review themes around comparable books.

🏫 Libraries can enrich catalog analysis with ratings and public reader feedback.

📈 Market researchers can compare reader sentiment across genres and authors.

🛒 Book marketers can build review exports for campaign planning.

### Why use this Goodreads scraper?

It accepts direct Goodreads book URLs for precise targeting.

It also accepts search queries and resolves matching public book pages.

It returns clean fields such as `bookTitle`, authors, ratings, review counts, reviewer names, review text, and visible engagement counts.

It is designed with low default limits so first test runs stay inexpensive.

### What Goodreads data can you extract?

| Category | Example fields |
| --- | --- |
| Book identity | `bookId`, `bookUrl`, `bookTitle` |
| Author data | `authors`, `authorUrls` |
| Metadata | `bookDescription`, `genres`, `coverUrl`, `bookFormat`, `numberOfPages`, `inLanguage` |
| Ratings | `averageRating`, `ratingsCount`, `reviewsCount` |
| Reviews | `reviewId`, `reviewUrl`, `reviewerName`, `reviewerUrl`, `rating`, `reviewText` |
| Engagement | `likesCount`, `commentsCount` |

### Pricing

This Actor uses Apify pay-per-event pricing. The prices below come from the current Actor pricing configuration. Apify public plans map to Store discount tiers, so the table shows both the user-facing plan context and the pricing tier name. The final price shown in Apify depends on the user account plan and any custom agreement.

| Event | What is charged | Price |
| --- | --- | ---: |
| `start` | One-time fee per run | $0.005 |

| Event | What is charged | Free / no discount | Starter / Bronze | Scale / Silver | Business / Gold | Custom / Platinum | Custom / Diamond |
| --- | --- | ---: | ---: | ---: | ---: | ---: | ---: |
| `item` | Per book metadata row or reader review row produced | $1.15 / 1,000 | $1 / 1,000 | $0.78 / 1,000 | $0.6 / 1,000 | $0.4 / 1,000 | $0.28 / 1,000 |

Each saved dataset row is one billable `item`: a book metadata row and each saved reader review row are charged separately. Apify may also charge platform usage for compute, storage, proxies, or data transfer outside this Actor pricing. Check the Actor run and the Apify Pricing tab for the exact cost shown to your account.

### Quick start

1. Open the actor on Apify.

2. Add one or more Goodreads book URLs.

3. Optionally add search queries such as `the great gatsby`.

4. Choose whether to include reviews.

5. Set `maxReviewsPerBook`.

6. Run the actor.

7. Download the dataset as JSON, CSV, Excel, or through the API.

### Input example

Use this compact direct-book request for a first run:

```json
{
  "bookUrls": [{ "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby" }],
  "includeReviews": true,
  "maxReviewsPerBook": 5
}
```

### Input: Goodreads book URLs

Use `bookUrls` when you already know the exact Goodreads pages.

Example:

```json
{
  "bookUrls": [
    { "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby" }
  ],
  "includeReviews": true,
  "maxReviewsPerBook": 10
}
```

### Input: search queries

Use `queries` when you want the actor to find matching public Goodreads books first.

Example:

```json
{
  "queries": ["the great gatsby"],
  "includeReviews": true,
  "maxReviewsPerBook": 5
}
```

### Input settings

| Field | Type | Description |
| --- | --- | --- |
| `bookUrls` | array | Goodreads book pages to scrape |
| `queries` | array | Goodreads book searches to resolve |
| `includeReviews` | boolean | Save public review rows |
| `maxReviewsPerBook` | integer | Review cap per book page |
| `maxRunSeconds` | integer | Optional 35–270 second safety budget; saved rows remain available when the actor stops before the deadline |
| `proxyConfiguration` | object | Optional Apify Proxy settings |

### Output example

```json
{
  "itemType": "book",
  "bookId": "41733839",
  "bookUrl": "https://www.goodreads.com/book/show/41733839-the-great-gatsby",
  "bookTitle": "The Great Gatsby",
  "authors": ["F. Scott Fitzgerald"],
  "averageRating": 3.93,
  "ratingsCount": 6067294,
  "reviewsCount": 136391
}
```

### Output fields

Book rows use `itemType`, `bookId`, `bookUrl`, `bookTitle`, `authors`, `bookDescription`, `genres`, `averageRating`, `ratingsCount`, `reviewsCount`, `coverUrl`, `bookFormat`, `numberOfPages`, and `inLanguage`. Review rows use `itemType`, `bookId`, `bookUrl`, `bookTitle`, `reviewId`, `reviewUrl`, `reviewerName`, `reviewerUrl`, `rating`, `reviewText`, `dateRead`, `dateAdded`, `likesCount`, and `commentsCount`.

### Review output example

```json
{
  "itemType": "review",
  "bookId": "41733839",
  "bookTitle": "The Great Gatsby",
  "reviewerName": "Nataliya",
  "rating": 5,
  "reviewText": "Public review text visible on Goodreads..."
}
```

### Tips for better results

Use direct Goodreads book URLs when accuracy matters most.

Keep `maxReviewsPerBook` low while testing.

Run several smaller jobs instead of one very large exploratory job.

Use query mode for discovery, then re-run with selected direct URLs.

Disable reviews when you only need metadata and aggregate ratings.

### Integrations

Send exported Goodreads review data to Google Sheets for editorial review.

Load CSV exports into Airtable to tag books by genre, rating, and sentiment.

Push JSON results into a warehouse for trend dashboards.

Connect the actor to Make or Zapier through Apify webhooks.

Use Apify API clients to schedule recurring monitoring of selected titles.

### API usage

#### Node.js

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

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('YOUR_USERNAME/goodreads-books-reviews-scraper').call({
  bookUrls: [{ url: 'https://www.goodreads.com/book/show/41733839-the-great-gatsby' }],
  includeReviews: true,
  maxReviewsPerBook: 5,
});
console.log(run.defaultDatasetId);
```

#### Python

```python
from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('YOUR_USERNAME/goodreads-books-reviews-scraper').call(run_input={
    'queries': ['the great gatsby'],
    'includeReviews': True,
    'maxReviewsPerBook': 5,
})
print(run['defaultDatasetId'])
```

#### cURL

```bash
curl -X POST 'https://api.apify.com/v2/acts/YOUR_USERNAME~goodreads-books-reviews-scraper/runs?token=APIFY_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"queries":["the great gatsby"],"includeReviews":true,"maxReviewsPerBook":5}'
```

### MCP usage

Use this actor from Claude Desktop or Claude Code through the Apify MCP server.

MCP URL pattern:

```text
https://mcp.apify.com/?tools=YOUR_USERNAME/goodreads-books-reviews-scraper
```

Claude Code setup:

```bash
claude mcp add apify --transport http https://mcp.apify.com
```

Claude Desktop-compatible configuration:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com"
    }
  }
}
```

Example prompt:

```text
Run the Goodreads Books & Reviews Scraper for The Great Gatsby and summarize recurring reader complaints from the first 20 reviews.
```

### Data quality notes

Goodreads page layouts can vary by book.

Some fields may be null when Goodreads does not show them publicly.

Review dates and engagement counts are saved only when visible on the public page.

Search queries may return several matching editions.

### Legal and ethical use

This actor extracts publicly available Goodreads pages.

You are responsible for using the results in line with applicable laws, Goodreads terms, and privacy rules.

Do not use scraped data for spam, harassment, or invasive profiling.

Respect reasonable limits and avoid unnecessary high-volume runs.

### Troubleshooting: no results

Check that the Goodreads URL is public and starts with `/book/show/`.

Try a direct book URL instead of a broad query.

Lower the review cap and run again.

If your network is blocked, enable Apify Proxy in the input.

### Troubleshooting: missing reviews

Some books show fewer public review cards than their aggregate review count.

Goodreads may personalize, paginate, or hide parts of the review list.

The actor saves public review cards visible in the fetched page.

### FAQ

#### Can I scrape private Goodreads shelves?

No. This actor is for public book pages and public review content only.

#### Can I scrape every review for a popular book?

The first version focuses on visible public review cards with a per-book cap. Use reasonable caps for cost control.

#### Can I search by ISBN?

If Goodreads autocomplete resolves the ISBN query to a public book page, the actor can scrape that page.

#### Does it require a Goodreads account?

No account is required for the public data targeted by this actor.

### Related scrapers

- [Shopify App Reviews Scraper](https://apify.com/fetch_cat/shopify-app-reviews-scraper)
- [Apple App Store Reviews Scraper](https://apify.com/fetch_cat/apple-app-store-reviews-scraper)
- [Product Hunt Scraper](https://apify.com/fetch_cat/product-hunt-scraper)

### Support

If a run fails or returns unexpected public book data, open an issue from the Actor page and include the Apify run ID or run URL, input JSON, expected output, actual output, and one reproducible public URL.

### Privacy and data handling

This Actor only requests the permissions needed to run the input you provide. It uses your input (such as URLs, search terms, identifiers, filters, and limits) only to fetch the requested public data from the relevant source site or API for this Actor, then writes results to your Apify dataset/key-value store.

Data may pass through Apify platform services and Apify Proxy during the run, and requests are sent only to the target site or public data provider required for this Actor's results. FetchCat does not send your inputs or outputs to advertising networks, data brokers, or model-training services, and does not retain run data outside Apify storage after the run except when you explicitly share run details for transient support debugging.

You are responsible for using this Actor lawfully, respecting the target site's terms, and avoiding unnecessary personal or sensitive data in inputs. Review the output before storing, sharing, or combining it with other data.

# Actor input Schema

## `bookUrls` (type: `array`):

Public Goodreads book pages to scrape. Add one or more /book/show/ URLs.

## `queries` (type: `array`):

Optional Goodreads book searches. The actor uses Goodreads autocomplete and scrapes the top public book pages for each query.

## `includeReviews` (type: `boolean`):

Save public reader reviews visible on the book page in addition to the book metadata row.

## `maxReviewsPerBook` (type: `integer`):

Maximum number of public reviews to save from each book page.

## `maxRunSeconds` (type: `integer`):

Optional safety budget from 35 to 270 seconds. The actor stops admitting new pages before the budget ends and keeps saved rows available.

## `proxyConfiguration` (type: `object`):

Optional Apify Proxy settings. Start without proxies; enable Apify Proxy only if Goodreads blocks your network.

## Actor input object example

```json
{
  "bookUrls": [
    {
      "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby"
    }
  ],
  "queries": [
    "the great gatsby"
  ],
  "includeReviews": true,
  "maxReviewsPerBook": 10,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

## `runSummary` (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 = {
    "bookUrls": [
        {
            "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby"
        }
    ],
    "queries": [
        "the great gatsby"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("fetch_cat/goodreads-books-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 = {
    "bookUrls": [{ "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby" }],
    "queries": ["the great gatsby"],
}

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

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

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

```

## CLI example

```bash
echo '{
  "bookUrls": [
    {
      "url": "https://www.goodreads.com/book/show/41733839-the-great-gatsby"
    }
  ],
  "queries": [
    "the great gatsby"
  ]
}' |
apify call fetch_cat/goodreads-books-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=fetch_cat/goodreads-books-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/P1Sc5uBAKYfLYQ6xo/builds/EbbzuruN3RjVCIynH/openapi.json