# Open Library Books Search (`scrupulous_waterbird_m4w/open-library-books`) Actor Search 40M+ books on Open Library by title, author, ISBN, or subject via the public JSON API. Returns structured records with publishers, publication years, ISBNs, page counts, language, and cover art. CC0 data. - **URL**: https://apify.com/scrupulous\_waterbird\_m4w/open-library-books.md - **Developed by:** [Mori](https://apify.com/scrupulous_waterbird_m4w) (community) - **Categories:** Developer tools, Other, Education - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use 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 ## Open Library Books Search Search the [Open Library](https://openlibrary.org) catalog — 40M+ books, 500M+ editions — directly via the public JSON API. No API key, no proxy, no scraping. Returns structured records with publishers, publication years, ISBNs, page counts, languages, subjects, and cover art. ### Why this actor Open Library is the Internet Archive's open bibliographic data project. The data is CC0 (public domain) where possible, and the `/search.json` endpoint is unauthenticated and keyless. Existing Apify scrapers in this niche scrape HTML pages page-by-page; this actor wraps the JSON API end-to-end — cleaner, faster, and structured from the source. ### Input | Field | Type | Default | Notes | |---|---|---|---| | `queries` | `string[]` | `["tolkien","haruki murakami","agatha christie"]` | One row per query. Free-form: titles, authors, ISBNs, subjects. | | `limit` | `integer` (1-50) | `10` | Max records per query. | | `sort` | `enum` (`relevance` / `new` / `old`) | `relevance` | `new`/`old` sort by first publish year. | | `languageFilter` | `string[]` | `[]` | Optional ISO-639-3 codes (e.g. `["eng","fre"]`). | | `fields` | `string[]` | curated subset | Advanced: override the Open Library `fields` query param. | ### Output (one record per matched book) ```jsonc { "query": "tolkien", "workKey": "/works/OL27448W", "title": "The Lord of the Rings", "authors": "J.R.R. Tolkien", "firstPublishYear": "1954", "publishYears": "1954; 1965; 1966; 1967; ...", "isbn": "9780739409558; 0261103938; 0395604230; ...", "publishers": "Houghton Mifflin; HarperCollins; ...", "subjects": "Fiction; Fantasy fiction; Middle Earth (Imaginary place); ...", "languages": "eng; fre; spa; ger; ...", "editionCount": "251", "pageCountMedian": "1193", "coverId": "14625765", "coverUrl": "https://covers.openlibrary.org/b/id/14625765-L.jpg", "openLibraryWorkUrl": "https://openlibrary.org/works/OL27448W", "fetchedAt": "2026-07-10T18:42:00.000Z" } ```` ### Why it works without a proxy Open Library's `/search.json` endpoint serves all datacenter IPs. We send a polite, identifiable `User-Agent` so the Internet Archive can contact the operator if ever needed. If you scale up to hundreds of queries per minute, register for their [API keys](https://openlibrary.org/dev/docs/api/search) and add a `User-Agent` header — the free tier is enough for actor-scale traffic. ### License Open Library data is CC0 where possible. The actor source is MIT. # Actor input Schema ## `queries` (type: `array`): List of search queries (titles, authors, ISBNs, or free-form). Each query produces up to `limit` records. Example: \['tolkien', 'haruki murakami', 'agatha christie', '9780261102385']. ## `limit` (type: `integer`): Maximum number of book records to return per query. Capped at 50 because the Open Library search index only returns up to ~100 per page; we cap conservatively. ## `sort` (type: `string`): Sort the results before slicing. 'relevance' (default) is the search-index score; 'new' sorts by descending first\_publish\_year; 'old' sorts by ascending first\_publish\_year. ## `languageFilter` (type: `array`): Optional list of ISO-639-3 language codes to keep (e.g. \['eng','fre','spa']). Leave empty for no language filter. ## `fields` (type: `array`): Optional override of Open Library's `fields` parameter. Defaults to a curated subset; pass a custom list only if you know the full field vocabulary. ## Actor input object example ```json { "queries": [ "tolkien", "haruki murakami", "agatha christie" ], "limit": 10, "sort": "relevance", "languageFilter": [], "fields": [] } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrupulous_waterbird_m4w/open-library-books").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scrupulous_waterbird_m4w/open-library-books").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 '{}' | apify call scrupulous_waterbird_m4w/open-library-books --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrupulous_waterbird_m4w/open-library-books", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Open Library Books Search", "description": "Search 40M+ books on Open Library by title, author, ISBN, or subject via the public JSON API. Returns structured records with publishers, publication years, ISBNs, page counts, language, and cover art. CC0 data.", "version": "0.0", "x-build-id": "cyiPAx5cCeaYfvMLN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrupulous_waterbird_m4w~open-library-books/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrupulous_waterbird_m4w-open-library-books", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrupulous_waterbird_m4w~open-library-books/runs": { "post": { "operationId": "runs-sync-scrupulous_waterbird_m4w-open-library-books", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrupulous_waterbird_m4w~open-library-books/run-sync": { "post": { "operationId": "run-sync-scrupulous_waterbird_m4w-open-library-books", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "queries" ], "properties": { "queries": { "title": "Search queries", "type": "array", "description": "List of search queries (titles, authors, ISBNs, or free-form). Each query produces up to `limit` records. Example: ['tolkien', 'haruki murakami', 'agatha christie', '9780261102385'].", "default": [ "tolkien", "haruki murakami", "agatha christie" ] }, "limit": { "title": "Max records per query", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of book records to return per query. Capped at 50 because the Open Library search index only returns up to ~100 per page; we cap conservatively.", "default": 10 }, "sort": { "title": "Sort order", "enum": [ "relevance", "new", "old" ], "type": "string", "description": "Sort the results before slicing. 'relevance' (default) is the search-index score; 'new' sorts by descending first_publish_year; 'old' sorts by ascending first_publish_year.", "default": "relevance" }, "languageFilter": { "title": "Filter by language (3-letter codes)", "type": "array", "description": "Optional list of ISO-639-3 language codes to keep (e.g. ['eng','fre','spa']). Leave empty for no language filter.", "default": [] }, "fields": { "title": "Fields to include (advanced)", "type": "array", "description": "Optional override of Open Library's `fields` parameter. Defaults to a curated subset; pass a custom list only if you know the full field vocabulary.", "default": [] } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```