Goodreads Scraper — Books, Authors, Ratings, Reviews & Leads

Extract complete Goodreads book data — titles, series, ISBN/ISBN-13/ASIN, format, page count, publisher, publication dates, genres, full descriptions, cover images, average rating with the full 1–5★ breakdown, ratings & review counts, per-language review counts, literary awards, settings/places, characters and the Amazon buy link. Pull community reviews for any book, and turn every author into a ready-to-contact lead with follower counts, ratings, books, bio, personal website, socials and emails.

No login, no cookies, no browser — fast JSON extraction from Goodreads' own page data.

Why this Goodreads scraper?

Most Goodreads scrapers only read the visible card (title, author, average rating) and stop at the search box — which Goodreads blocks. This actor pulls the full __APOLLO_STATE__ GraphQL cache behind every book page and ships the richest dataset in the category, with built-in keyword search that works around the blocked search page.

Data	Typical scrapers	This actor
Title, author, average rating	✅	✅
Full 1–5★ rating distribution	❌	✅
ISBN / ISBN-13 / ASIN	partial	✅
Format, pages, publisher, publication dates	partial	✅
Genres / shelves	partial	✅
Literary awards & Goodreads Choice Awards	❌	✅
Settings (places) & characters	❌	✅
Series & position	❌	✅
Per-language review counts	❌	✅
Community reviews (rating, text, likes, reviewer)	❌	✅ opt-in
Author leads (followers, website, socials, emails)	❌	✅ opt-in
Lead score (0–100) per author	❌	✅
Keyword search (Goodreads blocks /search)	❌	✅ auto-complete workaround
Monitor mode — only new records	❌	✅

Use cases

• Author & publishing lead generation — every author becomes a scored lead with follower count, ratings, books, personal website, socials and (with enrichment) emails. Perfect for book-marketing, editing, cover-design, PR and ad agencies selling to authors.
• Book data & catalog enrichment — feed apps, recommendation engines and databases with clean book metadata: ISBN/ASIN, genres, page counts, publishers, covers, ratings and descriptions.
• Market & competitive intelligence — track ratings, the full star distribution, review volume and award status across a genre, series or comp-title set.
• Reader sentiment & review mining — collect community reviews (rating, full text, likes, shelves) for sentiment analysis, comp research or marketing quotes.
• New-release & bestseller monitoring — schedule recurring runs over a genre, list or author and capture only newly listed books with monitor mode.

How to use

1. Sign up for Apify — the free plan is enough to try this actor.
2. Open the Goodreads Scraper, enter search queries or paste book/author/list/genre URLs, and click Start.
3. Watch results stream into the dataset table as each record is parsed.
4. Export as JSON, CSV, Excel, XML, or RSS — or pull results programmatically via the Apify API.

Input

{
    "searchQueries": ["project hail mary", "brandon sanderson"],
    "startUrls": [
        { "url": "https://www.goodreads.com/list/show/1.Best_Books_Ever" },
        { "url": "https://www.goodreads.com/author/show/153394.Suzanne_Collins" }
    ],
    "bookIds": ["2767052", "9780593135204"],
    "maxBooks": 50,
    "includeReviews": true,
    "maxReviewsPerBook": 20,
    "outputAuthorLeads": true,
    "enrichAuthorWebsites": true,
    "monitorMode": false,
    "monitorKey": "default"
}

• searchQueries — book titles, author names or ISBNs, looked up via Goodreads' open auto-complete (each query returns its top matches, scraped in full).
• startUrls — Goodreads URLs: book pages (/book/show/…), author pages (/author/show/…), Listopia lists (/list/show/…), genre/shelf pages (/genres/…, /shelf/show/…) and series pages (/series/…). Lists/genres/series/authors are expanded into their books.
• bookIds — Goodreads numeric IDs or ISBN-10/ISBN-13.
• maxBooks (default 50) — cap on book records; reviews and author leads are additional.
• includeReviews / maxReviewsPerBook — also output the community reviews embedded on each book page (up to ~30 each).
• outputAuthorLeads (default false) — output one deduplicated lead record per author found.
• enrichAuthorWebsites (default false) — crawl each author's personal website (home + contact/about) for emails, phones and socials.
• includeAuthorBooks (default true) — when an author URL is given, also scrape the books on that page.
• monitorMode / monitorKey — emit only records new since the last run (see Monitoring).

Output

One record per book (type: "book"), plus optional review records (type: "review") and author lead records (type: "author"):

{
    "type": "book",
    "bookId": "2767052",
    "title": "The Hunger Games",
    "titleComplete": "The Hunger Games (The Hunger Games, #1)",
    "url": "https://www.goodreads.com/book/show/2767052-the-hunger-games",
    "description": "Winning means fame and fortune. Losing means certain death…",
    "imageUrl": "https://images-na.ssl-images-amazon.com/images/.../2767052.jpg",
    "primaryAuthor": "Suzanne Collins",
    "authors": [
        { "name": "Suzanne Collins", "id": "153394", "url": "https://www.goodreads.com/author/show/153394.Suzanne_Collins", "role": "Author", "followersCount": 128590 }
    ],
    "series": [{ "name": "The Hunger Games", "url": "https://www.goodreads.com/series/73758-the-hunger-games", "position": "1" }],
    "genres": ["Young Adult", "Dystopia", "Fiction", "Fantasy", "Science Fiction"],
    "format": "Hardcover",
    "numPages": 374,
    "isbn": "0439023483",
    "isbn13": "9780439023481",
    "asin": "0439023483",
    "publisher": "Scholastic Press",
    "language": "English",
    "publicationDate": "2008-10-14T07:00:00.000Z",
    "averageRating": 4.35,
    "ratingsCount": 10140474,
    "reviewsCount": 271369,
    "ratingDistribution": { "1": 133268, "2": 241455, "3": 1110224, "4": 3075882, "5": 5579645 },
    "places": ["District 12, Panem", "Capitol, Panem"],
    "characters": ["Katniss Everdeen", "Peeta Mellark"],
    "awards": [{ "name": "Locus Award", "category": "Best Young Adult Book", "year": 2009 }],
    "workId": "2792775",
    "buyUrl": "https://www.amazon.com/gp/product/...",
    "ebookPrice": 5.99,
    "scrapedAt": "2026-06-17T12:00:00.000Z"
}

Author lead record (type: "author"):

{
    "type": "author",
    "authorId": "153394",
    "name": "Suzanne Collins",
    "url": "https://www.goodreads.com/author/show/153394.Suzanne_Collins",
    "website": "http://suzannecollinsbooks.com/",
    "followersCount": 128590,
    "averageRating": 4.35,
    "ratingsCount": 21389320,
    "bookCount": 69,
    "genres": ["Young Adult", "Science Fiction & Fantasy", "Fiction"],
    "born": "August 11, 1962",
    "emails": ["contact@suzannecollinsbooks.com"],
    "socials": { "twitter": "https://twitter.com/..." },
    "leadScore": 78,
    "scrapedAt": "2026-06-17T12:00:00.000Z"
}

Fields are null/omitted only when Goodreads genuinely doesn't publish them (e.g. an online-only edition has no ISBN, a translator-only contributor, an author with no website). Empty results are reported as success.

Monitoring — get only new books, reviews & authors

Turn on monitorMode to remember the IDs seen in previous runs (in a named key-value store, goodreads-monitor-<monitorKey>) and emit only records that are new since the last run — new books in a genre, new reviews on a title, or newly discovered authors. Set a distinct monitorKey per search so different watches keep separate memory. This is fully compatible with Apify Schedules: the schedule triggers the run, monitor mode deduplicates the output.

Automate & schedule

Run this actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets, and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it on a cron to keep your data fresh.
• Webhooks — trigger downstream actions the moment a run finishes.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });

const run = await client.actor('scrapesage/goodreads-scraper').call({
    searchQueries: ['project hail mary'],
    startUrls: [{ url: 'https://www.goodreads.com/list/show/1.Best_Books_Ever' }],
    maxBooks: 50,
    includeReviews: true,
    outputAuthorLeads: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} records`);

Integrate with any app

Connect the dataset to 5,000+ apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new records straight into your CRM or sheet.
• Slack — get notified when a run finds something new.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the Apify MCP server — ask your assistant to "find the top fantasy books on Goodreads with their ratings and author contacts" and let it run this scraper for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

More scrapers from scrapesage

Build a complete author, creator & content lead-gen stack:

• Substack Scraper — newsletters, posts and writer/creator leads.
• Apple Podcasts Scraper — shows, episodes, reviews and host leads.
• YouTube Scraper — channels, videos and creator leads.
• Product Hunt Scraper — launches, makers and community leads.
• Telegram Scraper — channels, messages, media and search.
• Facebook Ad Library Scraper — competitor ad intelligence for book marketing.
• Eventbrite Scraper — events plus organizer leads with contacts.
• Airbnb Scraper — short-stay listings, prices and availability.

Tips

• Bulk discovery: keyword search returns each query's top auto-complete matches. For hundreds of books, paste Listopia list, genre/shelf or author URLs in startUrls — each is expanded into its books up to maxBooks.
• Reviews: each book page carries up to ~30 community reviews; set maxReviewsPerBook to control how many you keep.
• Author emails: turn on enrichAuthorWebsites — Goodreads never exposes emails, so the actor visits each author's own public website to find them.
• Proxies: the default Apify datacenter proxy works well; switch to Residential only if you push very high volume and hit rate challenges.
• Cost control: author leads are deduplicated, and website enrichment only runs for authors who actually list a website.

FAQ

Can I search Goodreads by keyword? Yes. Goodreads blocks its own /search page to bots, so this actor uses the open book auto-complete endpoint for keyword lookups, and supports Listopia list, genre, series and author URLs for bulk discovery.

Does it need a Goodreads login or API key? No. Goodreads retired its public API, but this actor extracts the same (and richer) data directly from public pages — no key, login, or browser.

What about ISBNs? Put ISBN-10 or ISBN-13 values in bookIds (or as search queries) and the actor resolves them to full book records.

Can I export to Google Sheets, CSV, or Excel? Yes — one click in the dataset view, or automatically on every run via the Google Drive integration.

How do I monitor new releases automatically? Turn on monitorMode, give it a monitorKey, and create a Schedule; only books/reviews/authors new since the last run are emitted.

Where do author emails come from? Never from Goodreads. With enrichAuthorWebsites on, the actor visits the author's own public website and extracts publicly listed contact details — the same thing a visitor would see.

Is scraping Goodreads legal? This actor collects publicly available data only. You are responsible for using the data in compliance with applicable laws (GDPR/CCPA for personal data) and Goodreads' terms.

Need help?

Open an issue on the actor's Issues tab, or visit the Apify help center. Feature requests are welcome — this actor is actively maintained.