# 📚 Goodreads Book Search Scraper (`hipersoft/goodreads-scraper`) Actor

Search Goodreads and export clean book data in bulk — title, author, average rating, ratings count, cover image and book URL. Enter any keywords (or paste Goodreads search URLs) and download the results as JSON, CSV or Excel.

- **URL**: https://apify.com/hipersoft/goodreads-scraper.md
- **Developed by:** [hiper soft](https://apify.com/hipersoft) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.0015 / book scraped

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/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

## 📚 Goodreads Book Search Scraper

Search **Goodreads** and export the results as clean, structured **JSON, CSV, Excel or XML**. Enter any keywords — a book title, author, series or topic — and this actor returns one tidy row per book: **title, author, average rating, ratings count, cover image** and the **Goodreads book URL**. Perfect for building reading lists, market and genre research, catalog enrichment and recommendation data.

### What does Goodreads Book Search Scraper do?

This actor turns Goodreads search results into a ready-to-use dataset. Type one or more search keywords (or paste Goodreads search URLs straight from your browser), and it walks every page of each search and collects each book with structured fields. No manual copy-paste, no page-by-page clicking — just clean rows you can sort, filter and analyse.

### What data can you get?

**Per book:**

| Field | Description |
| --- | --- |
| `bookId` | Goodreads book reference number. |
| `title` | Book title. |
| `author` | Primary author name. |
| `avgRating` | Average rating (0–5) as a number. |
| `ratingsCount` | Total number of ratings. |
| `url` | Link to the book's Goodreads page. |
| `coverImage` | Cover image URL, when present. |
| `sourceQuery` | The search keyword the book was found under. |

### Use cases

- **Reading lists** — build curated lists by topic, author or genre.
- **Market & genre research** — compare ratings and popularity across titles.
- **Catalog enrichment** — add ratings, authors and covers to your own book data.
- **Recommendation data** — feed structured book data into your own models.
- **Dashboards** — power reports from clean, structured rows.
- **Automation** — pull fresh book data into your pipelines on a schedule.

### How to use it

1. Add **Goodreads Book Search Scraper** to your Apify account and open its input.
2. Enter one or more **Search keywords** (e.g. `dune`, `stephen king`, `cozy mystery`), or paste Goodreads search URLs.
3. Set **Max items** to cap the output.
4. Click **Run**.
5. Export the results as JSON, CSV, Excel or XML.

### Input

```json
{
  "queries": ["dune"],
  "maxItems": 100
}
```

| Field | Description |
| --- | --- |
| `queries` | One or more search keywords to look up. |
| `startUrls` | Optional Goodreads search URLs to scrape instead of, or alongside, keywords. |
| `maxItems` | Cap the number of books. `0` = no limit. |
| `maxConcurrency` | How many requests to run in parallel. |

### What you get

One flat JSON row per book, ready to export to CSV, Excel, JSON or XML.

```json
{
  "bookId": "44767458",
  "title": "Dune (Dune, #1)",
  "author": "Frank Herbert",
  "avgRating": 4.27,
  "ratingsCount": 1382241,
  "url": "https://www.goodreads.com/book/show/44767458",
  "coverImage": "https://images-na.ssl-images-amazon.com/images/S/compressed.photo.goodreads.com/books/1555447414i/44767458.jpg",
  "sourceQuery": "dune"
}
```

### FAQ

**What can I search for?**
Anything you would type into the Goodreads search box — a book title, an author, a series or a general topic. Each keyword is searched and paginated automatically.

**How many books can I collect?**
Use **Max items** to set any cap you like, or `0` for no limit. The actor paginates through the results until it reaches your cap or runs out of matches.

**Can I scrape several searches at once?**
Yes — add as many keywords (or search URLs) as you like and they are all collected into one dataset, each row tagged with its `sourceQuery`.

**What export formats are supported?**
JSON, CSV, Excel and XML — plus the Apify API and integrations for automation.

# Actor input Schema

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

One or more search terms to look up on Goodreads — a book title, author, series or topic (e.g. "dune", "stephen king", "cozy mystery"). Each keyword is searched and paginated automatically.

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

Optional: paste Goodreads search result URLs straight from your browser (e.g. https://www.goodreads.com/search?q=dune). Use this instead of, or in addition to, the keywords above.

## `maxItems` (type: `integer`):

Maximum number of books to collect across all searches (0 = no limit; collect everything the searches return).

## `maxConcurrency` (type: `integer`):

How many requests to run in parallel. Leave at the default unless you have a reason to change it.

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

Optional proxy settings. Not required — leave off for the default direct connection.

## Actor input object example

```json
{
  "queries": [
    "dune"
  ],
  "maxItems": 100,
  "maxConcurrency": 5
}
```

# Actor output Schema

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

The results as dataset items.

# 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 = {
    "queries": [
        "dune"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("hipersoft/goodreads-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 = { "queries": ["dune"] }

# Run the Actor and wait for it to finish
run = client.actor("hipersoft/goodreads-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 '{
  "queries": [
    "dune"
  ]
}' |
apify call hipersoft/goodreads-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hipersoft/goodreads-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/QlK8POZQ20SOwp8p0/builds/ekIPe7Yw1g38WHtCt/openapi.json