# Open Library Books and Author Metadata Radar (`adaptive_nightmare/open-library-books-radar`) Actor

Extract Open Library Books and Author Metadata data in clean JSON or CSV. Query by query, author, subject for records, engagement metrics, and metadata. Export datasets, run via API or Python/Node.js SDK, schedule runs, or integrate with webhooks with zero proxy fees.

- **URL**: https://apify.com/adaptive_nightmare/open-library-books-radar.md
- **Developed by:** [Darim Quraishi](https://apify.com/adaptive_nightmare) (community)
- **Categories:** Education, Developer tools, AI
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.05 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Open Library Books and Author Metadata Radar

Search millions of digitized books, author bibliographies, ISBN numbers, publication years, and cover artwork from the Internet Archive Open Library.

### Features

- Queries the comprehensive Open Library catalog covering both modern publications and historical public domain works.
- Retrieves verified book titles, primary authors, first publication years, and total edition counts.
- Gathers international standard book numbers (ISBN-10 and ISBN-13), publisher lists, and subject classifications.
- Generates high resolution direct links to cover artwork images hosted on Open Library media servers.
- Operates via public JSON endpoints without API registration tokens or proxy configurations.
- Delivers clean records formatted for export to JSON, CSV, Excel, or automated digital library pipelines.

### Input parameters

- Search Query: Title, topic, or keyword phrase to query across the catalog. Default is machine learning.
- Author Name Filter: Optional filter to restrict results to a specific writer or editor.
- Subject Tag Filter: Optional thematic classification (such as artificial_intelligence or science_fiction).
- Sort Order: Order results by relevance, newest first, oldest first, or most published editions. Default is relevance.
- Maximum Books: Maximum number of book records to collect, up to 100. Default is 25.

### Output dataset fields

Each dataset record contains:

- key: Unique Open Library resource path (for example: /works/OL27479W).
- title: Complete book title and subtitle.
- authorNames: Array of contributing author names.
- firstPublishYear: Earliest recorded calendar year of publication.
- editionCount: Total separate printings and editions indexed by Open Library.
- isbns: Array of validated ISBN identifiers.
- publishers: Primary publishing houses and presses associated with the work.
- languages: Array of available translation languages.
- subjects: Thematic taxonomy tags and Library of Congress subject categories.
- coverId: Numerical cover image identifier.
- coverUrl: High resolution image URL of the front book cover.
- openLibraryUrl: Direct link to the complete work profile on openlibrary.org.
- scrapedAt: UTC timestamp when the data was extracted.

### Use cases

- Catalog enrichment: Match local ISBN inventories against comprehensive bibliographic metadata.
- Bookstore inventory: Retrieve verified author listings, editions, and cover images for retail storefronts.
- LLM research: Ingest verified public domain book indices for literary analysis and educational reference.
- Reading apps: Power search bars and reading recommendation engines with zero proprietary database fees.

# Actor input Schema

## `query` (type: `string`):

Book title, topic, or general keyword to search (for example: machine learning, dune, clean code, or psychology).

## `author` (type: `string`):

Optional author name to narrow results (for example: Frank Herbert, Stuart Russell, or Martin Fowler).

## `subject` (type: `string`):

Optional subject classification (for example: computer_science, artificial_intelligence, or science_fiction).

## `sort` (type: `string`):

Result sorting criteria.

## `maxBooks` (type: `integer`):

Maximum number of book records to collect.

## Actor input object example

```json
{
  "query": "machine learning",
  "sort": "relevance",
  "maxBooks": 25
}
```

# Actor output Schema

## `results` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("adaptive_nightmare/open-library-books-radar").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("adaptive_nightmare/open-library-books-radar").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 '{}' |
apify call adaptive_nightmare/open-library-books-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,adaptive_nightmare/open-library-books-radar"
        }
    }
}
```

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/N48pUIjMXKDyadW73/builds/SY0VB9GX3LPmkyVZH/openapi.json