# Goodreads Email Scraper (`scraper-engine/goodreads-email-scraper`) Actor

Goodreads Email Scraper extracts publicly available email addresses from Goodreads author profiles and linked websites. Build targeted contact lists for publishing outreach, partnerships, and author communication.

- **URL**: https://apify.com/scraper-engine/goodreads-email-scraper.md
- **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community)
- **Categories:** Lead generation, Developer tools, Automation
- **Stats:** 5 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

$19.99/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

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

## 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** Email Scraper 📱

**Goodreads** Email Scraper enables users to **extract** publicly available **contact** information from **Goodreads** pages. This includes email addresses found in author bios, book-club group descriptions, and other relevant **data** points that can be used for research, marketing, or networking purposes.

The tool is designed to gather **data** efficiently while ensuring accuracy and compliance with legal standards. With this **Goodreads** email harvesting tool, you can customize the **data** **extract**ion process to suit your specific needs.

Whether you are looking for author contact emails, book-club organizer emails, or other public page details, this scraper provides a comprehensive solution. By automating the **data** collection process, it eliminates the need for manual effort, saving time and resources.

It is particularly useful for businesses, researchers, and developers who require structured **data** for analysis or outreach. The tool is compatible with various use cases, making it a versatile option for **data** **extract**ion from **Goodreads** pages.

Goodreads Email Scraper is a powerful tool designed to help you extract email addresses and other relevant data from Goodreads pages effortlessly. It is an ideal solution for businesses, researchers, and marketers looking to connect with authors, book clubs, and readers for various purposes.

With this Goodreads data extraction tool, you can automate the process of gathering contact information from public Goodreads pages. This saves time and ensures accuracy in collecting essential data for your needs.

Our Goodreads contact scraper is built to handle large-scale data extraction while maintaining compliance with ethical and legal guidelines. It is user-friendly and requires minimal technical expertise to operate.

### Support and feedback

- **Bug reports**: Open a ticket in the repository Issues section
- **Custom features**: Contact our enterprise support team
  *Email: dev.scraperengine@gmail.com*

### Extractable Data Table 📊

Each result row contains the following fields:

| Data Type | Description |
| --- | --- |
| network | Source platform (e.g. goodreads.com). |
| keyword | The keyword that produced this result. |
| title | Title of the result (usually the author/page name). |
| description | Snippet text from the result, which may contain contact info. |
| url | Direct URL to the Goodreads page. |
| email | Publicly available email address extracted from the result. |

### Key Features of **Goodreads** Email Scraper

Here are the **standout features** that make the **Goodreads** Email Scraper a **top-tier tool** for **marketers**, **agencies**, and **researchers**:

- ⭐ **Automated** data extraction from **Goodreads** pages for efficiency and accuracy
- ⭐ **Customizable** scraping options to target specific keywords and pages
- ⭐ User-friendly interface requiring minimal technical expertise to operate
- ⭐ **High**-speed data scraping capabilities for handling large datasets quickly
- ⭐ Compliance with ethical and legal standards for responsible data collection
- ⭐ Option to export extracted data in various formats such as CSV or JSON
- ⭐ Built-in error handling to ensure uninterrupted scraping sessions
- ⭐ **Secure** and reliable data extraction with minimal risk of account bans
- ⭐ **Regular** updates to maintain compatibility with **Goodreads** platform changes
- ⭐ Scalable solution suitable for both small-scale and enterprise-level data needs
- ⭐ Detailed documentation and support to assist users at every step
- ⭐ Multi-threading capabilities for faster and more efficient data extraction

### How to use **Goodreads** Email Scraper 🚀

Follow this **simple, step-by-step guide** to start extracting **Goodreads** emails today:

1. ✅ **Sign up** for the **Goodreads** Email Scraper on the Apify platform
2. ✅ Open the actor and go to the Input tab
3. ✅ **Configure** the keywords, location, and email domain filters you want
4. ✅ Enter the target keywords for data extraction (e.g. 'author', 'book club')
5. ✅ **Start** the scraping process and monitor the progress in real-time
6. ✅ **Review** the extracted data to ensure accuracy and completeness
7. ✅ **Export** the collected data in your preferred format for further use
8. ✅ Repeat the process as needed for additional keywords or data points
9. ✅ Adjust scraping settings for optimized performance based on your requirements
10. ✅ Refer to the documentation for troubleshooting or advanced configurations
11. ✅ Contact support if you encounter any issues or need assistance

### Use Cases 🎯

Marketing and Outreach
🎯 **Collect** email addresses for targeted marketing campaigns
🎯 **Identify** potential authors or collaborators on **Goodreads**
🎯 Build a database of **Goodreads** contacts for promotional outreach

Research and Analysis
🎯 Gather public page data for demographic or behavioral studies
🎯 **Analyze** **Goodreads** author and book-club activity
🎯 Extract book-related pages for literary research or trend analysis

Networking Opportunities
🎯 Connect with **Goodreads** authors and book clubs who share similar interests
🎯 **Identify** potential partners or collaborators in the literary community
🎯 Expand your professional network using **Goodreads** contact information

Data Enrichment
🎯 Enhance existing datasets with additional public information from **Goodreads**
🎯 Combine **Goodreads** data with other sources for comprehensive analysis
🎯 **Use** extracted data to improve CRM systems or marketing tools

### Why choose us? 💎

**Goodreads** Email Scraper is designed to provide a seamless and efficient data extraction experience. Our tool is built with user convenience in mind, offering an intuitive interface and customizable options.

Whether you are a marketer, researcher, or developer, our scraper caters to diverse needs with precision and reliability. We prioritize compliance with ethical and legal guidelines, ensuring that data collection is conducted responsibly.

Our software is **regular**ly updated to adapt to changes in the **Goodreads** platform, maintaining its effectiveness over time. With **advanced** features like multi-threading and error handling, our scraper delivers high-speed performance without compromising on quality.

We also offer detailed documentation and responsive support to address any questions or concerns. Choose **Goodreads** Email Scraper for a dependable and versatile solution to your data extraction needs.

By automating the process, you can save time and focus on leveraging the collected data for your goals. Trust our expertise to deliver a high-quality scraping experience tailored to your requirements.

### **Goodreads** Email Scraper Scalability 📈

The **Goodreads** Email Scraper is designed to handle data extraction at any scale. Whether you need to scrape a few pages or thousands, our tool is equipped to manage the workload **efficient**ly.

With multi-threading capabilities, it can process large datasets quickly and accurately. Our scraper is optimized for performance, ensuring that even high-volume tasks are completed without delays.

It is suitable for both small businesses and large enterprises, offering flexibility to meet varying demands. The tool's **customizable** settings allow you to tailor the scraping process to your specific requirements.

By leveraging automation, you can scale your data collection efforts without adding to your workload. **Goodreads** Email Scraper is a reliable solution for growing businesses and organizations looking to expand their data-driven strategies.

With regular updates and robust support, it remains a dependable choice for scalable data extraction from **Goodreads**.

### **Goodreads** Email Scraper Legal Guidelines ⚖️

**Yes**—scraping **Goodreads** is **legal** as long as you follow **ethical** and **compliant** practices. The **Goodreads** Email Scraper extracts only **publicly available** information from **public** **Goodreads** pages, making it **safe** and **compliant** for **research**, **marketing**, and **analysis**.

#### Legal & Ethical Guidelines

⚖️ **Ensure** compliance with **Goodreads** terms of service when using the scraper
⚖️ **Do not** use the scraper to collect data for malicious or unethical purposes
⚖️ **Obtain** user consent before using their contact information for outreach
⚖️ **Avoid** excessive scraping to prevent overloading the **Goodreads** servers
⚖️ **Use** the scraper responsibly to maintain the integrity of the **Goodreads** platform
⚖️ **Adhere** to data protection laws and regulations in your region
⚖️ **Do not** share or sell extracted data without proper authorization
⚖️ Regularly review **Goodreads** policies to stay updated on any changes

### Input Parameters 🧩

📦 Example Input (JSON)

```json
{
  "keywords": ["author", "book club"],
  "platform": "Goodreads",
  "location": "",
  "emailDomains": ["@gmail.com", "@outlook.com"],
  "maxEmails": 10,
  "engine": "legacy",
  "proxyConfiguration": { "useApifyProxy": false }
}
```

### Input Table

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| keywords | array | ✅ Yes | Keywords used to find relevant Goodreads pages. One or more. |
| platform | string | No | Platform to scrape. Currently `Goodreads`. |
| location | string | No | Optional location filter. Empty = global. |
| emailDomains | array | No | Keep only emails from these domains (e.g. `@gmail.com`). Custom/business domains supported. Empty = all domains. |
| maxEmails | integer | No | Max emails to collect per keyword (default `10`, range 1–100000). |
| engine | string | No | Processing engine. Currently `legacy`. |
| proxyConfiguration | object | No | Proxy settings. Empty = the actor auto-selects the best proxy (recommended). |

> ℹ️ Emails are sourced from publicly available information only. Yield depends heavily on **which pages actually carry a contact email**, not just on the keyword being "on topic". Goodreads' plain book pages (a single book's listing) almost never list a personal contact email — Goodreads is a book catalog and review community, not a marketplace of individual seller listings. The pages that *do* regularly carry contact emails are **author bio/profile pages** (many independent/self-published authors list a contact email or link a site that surfaces one) and **book-club/group pages** (organizers often post a contact email), so content-type keywords like `author` or `book club` consistently out-perform narrow marketing phrases. Broaden `keywords`, add relevant `emailDomains`, and raise `maxEmails` for more results.

### Output Format 📤

📝 Example Output (JSON)

```json
[
  {
    "network": "goodreads.com",
    "keyword": "author",
    "title": "Jane Author (Author of The Example Novel)",
    "description": "Jane Author is an independent novelist. For review copies or interviews, contact janeauthor@gmail.com.",
    "url": "https://www.goodreads.com/author/show/1234567.Jane_Author",
    "email": "janeauthor@gmail.com"
  }
]
```

### Output Table

| Data Type | Description |
| --- | --- |
| network | Source platform (goodreads.com) |
| keyword | Keyword that triggered the result |
| title | Result title (usually the author/page name) |
| description | Public snippet, may contain contact info |
| url | Direct Goodreads page link |
| email | Extracted email address |

### FAQ ❓

#### What is Goodreads **Email Scraper**?

Goodreads Email Scraper is a tool designed to extract email addresses and other public data from Goodreads pages for various purposes.

#### Is the Goodreads **Email Scraper** easy to use?

**Yes**, the scraper features a **user-friendly** interface and requires minimal technical expertise to operate.

#### What data can I **extract** using this tool?

You can extract publicly available email addresses along with the result title, snippet, and page URL for each match.

#### Is the Goodreads **Email Scraper** **legal** to use?

**Yes**, as long as you comply with Goodreads' terms of service and applicable data protection laws.

#### Can I customize the data **extract**ion process?

**Yes**, the scraper allows you to specify the keywords, location, and email domain filters you want.

#### How do I **export** the **extract**ed data?

You can export the data in various formats such as **CSV** or **JSON** for further use.

#### Is the scraper compatible with all devices?

The Goodreads Email Scraper runs on the Apify platform and is compatible with most modern operating systems and devices.

#### Can I scrape data from multiple keywords simultaneously?

**Yes**, the scraper supports multiple keywords per run for faster and more efficient data extraction.

#### What should I do if I encounter an error?

Refer to the documentation or contact our support team for assistance with troubleshooting.

#### Is there a **limit** to the number of pages I can scrape?

The scraper is scalable and can handle both small-scale and large-scale data extraction tasks.

#### Does the scraper offer regular updates?

**Yes**, we provide **regular updates** to ensure compatibility with Goodreads platform changes.

#### Can I use the scraper for marketing purposes?

**Yes**, you can use the scraper to collect data for targeted marketing campaigns, provided you comply with legal and ethical guidelines.

#### Is the data **extract**ion process **secure**?

**Yes**, the scraper is designed to ensure **secure** and reliable data extraction with minimal risk.

#### How long does it take to **extract** data?

The duration depends on the volume of data being scraped, but the scraper is optimized for high-speed performance.

#### Do I need a Goodreads account to use the scraper?

**No**, the scraper only collects **publicly available** information that is already publicly indexed online — no login is required.

# Actor input Schema

## `keywords` (type: `array`):

🎯 The words that power your search! Add one or more keywords and the actor finds public Goodreads pages matching them, then 📧 extracts any email addresses it finds. 💡 Tip: broad, content-type words like 'author' or 'book club' match real Goodreads pages (author bio pages, book-club group pages) that often list a contact email — narrow marketing phrases rarely appear verbatim on any page and return far fewer results.

## `platform` (type: `string`):

📱 The site to scrape. Currently locked to Goodreads — more platforms coming soon! 🚀

## `location` (type: `string`):

🗺️ Optional geo-targeting! Add a city or region (e.g. 'London' 🇬🇧, 'New York' 🗽, 'Dubai' 🏙️) to narrow results to pages mentioning that place. ✨ Leave empty to search the whole globe 🌍.

## `emailDomains` (type: `array`):

🎛️ Keep only emails from the domains you care about — type as many as you like! ✍️ Popular picks: 📮 @gmail.com · 📨 @outlook.com · 💌 @hotmail.com · 💜 @yahoo.com · ☁️ @icloud.com · 📬 @aol.com · 🔒 @protonmail.com · 📥 @live.com · 📧 @gmx.com · 🟡 @yandex.com · 📗 @zoho.com. 🏢 Custom/business domains work too — e.g. @yourcompany.com. 🕳️ Leave empty to collect emails from ALL domains. 💡 Adding a domain also sharpens the search 🎯.

## `maxEmails` (type: `integer`):

🎚️ How many emails to collect per keyword before moving on. ⚡ Higher = more leads but longer runs. Default is 10 ✅ (range 1 – 100,000).

## `engine` (type: `string`):

🔧 The processing engine. Currently 'legacy' 🛡️ — a reliable, battle-tested extraction pipeline. More engines on the roadmap! 🚧

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

🌐 Control how the actor connects to the internet. 🆓 Leave it empty and the actor auto-selects the best proxy for reliable results. 🔄 On any failed response it rotates the connection and retries up to 3× automatically. 🧠 Advanced users can plug in custom proxies here.

## Actor input object example

```json
{
  "keywords": [
    "author",
    "book club"
  ],
  "platform": "Goodreads",
  "location": "",
  "emailDomains": [
    "@gmail.com"
  ],
  "maxEmails": 10,
  "engine": "legacy",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# 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 = {
    "keywords": [
        "author",
        "book club"
    ],
    "emailDomains": [
        "@gmail.com"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scraper-engine/goodreads-email-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 = {
    "keywords": [
        "author",
        "book club",
    ],
    "emailDomains": ["@gmail.com"],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("scraper-engine/goodreads-email-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 '{
  "keywords": [
    "author",
    "book club"
  ],
  "emailDomains": [
    "@gmail.com"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call scraper-engine/goodreads-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scraper-engine/goodreads-email-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/QMx8EfZJTZLq8DGeI/builds/fu9LVaOPQ24tgoIuL/openapi.json