# Crossref Publications API Scraper – DOI, Title & Citations (`ahmdshrif/crossref-publications-scraper`) Actor Exports structured publication records (DOI, title, authors, journal, citation counts, and more) from the official Crossref REST API. - **URL**: https://apify.com/ahmdshrif/crossref-publications-scraper.md - **Developed by:** [Ahmed](https://apify.com/ahmdshrif) (community) - **Categories:** Developer tools, AI, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.00 / 1,000 publication record exporteds 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? 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 ## Crossref Publications API Scraper – DOI, Title & Citations Exports structured publication records — DOI, title, authors, journal, volume/issue, ISSN/ISBN, and citation counts — from the official Crossref REST API. Built for researchers, librarians, bibliometricians, and AI/data teams who need clean scholarly metadata or citation datasets without writing their own Crossref API client. ### Why this scraper - Reads Crossref's official JSON API directly rather than scraping rendered HTML pages, so every field Crossref publishes is captured in structured form, with no HTML parsing errors or layout-dependent guesswork. - Includes `referenceCount` and `isReferencedByCount` on every record, so citation-based analysis doesn't require a second lookup. - No personal or scraped-web data involved — output is limited to publication metadata that Crossref publishers already deposit publicly. ### Output fields | Field | Type | Description | |---|---|---| | doi | string | DOI identifier of the publication | | title | string | Title of the publication | | type | string | Crossref work type, e.g. journal-article, book-chapter, proceedings-article | | publisher | string | Name of the publisher | | containerTitle | string | Journal, book, or series title containing the work | | authors | string | Semicolon-separated list of author full names in order | | publishedDate | string | Publication date, YYYY, YYYY-MM, or YYYY-MM-DD | | volume | string | Volume number | | issue | string | Issue number | | page | string | Page range, e.g. 60-70 | | issn | string | Comma-separated ISSN(s) of the containing journal | | isbn | string | Comma-separated ISBN(s) of the work | | referenceCount | integer | Number of references listed in the work | | isReferencedByCount | integer | Number of times this work is cited according to Crossref | | url | string | Canonical doi.org URL for the work | | member | string | Crossref member ID of the depositing publisher | ### Input ```json { "startUrls": [{ "url": "https://api.crossref.org/works?rows=50" }], "maxItems": 50 } ``` You can point `startUrls` at any Crossref REST endpoint, such as `works`, `journals`, or `members`, with query parameters (filters, search terms, `rows`) included in the URL. `maxItems` caps the number of records exported. ### Output ```json { "doi": "10.1002/9781119584414.ch4", "title": "Complete Dental Cleaning", "type": "other", "publisher": "Wiley", "containerTitle": "Blackwell's Five-Minute Veterinary Consult Clinical Companion", "authors": "", "publishedDate": "2021-06-11", "volume": "", "issue": "", "page": "47-54", "issn": "", "isbn": "9781119584339,9781119584414", "referenceCount": 0, "isReferencedByCount": 0, "url": "https://doi.org/10.1002/9781119584414.ch4", "member": "311" } ``` ### Pricing Pay per result: **$0.001 per publication record exported** (~$1 per 1,000 records). A run pulling 50 records, like the example input above, costs $0.05. ### Use cases - Building a citation-count dataset for a bibliometrics study across a set of DOIs or a publisher's catalog. - Populating a university library or repository system with structured metadata (authors, ISSN/ISBN, volume/issue) for newly deposited works. - Feeding an AI research assistant or literature-review tool with clean title/author/journal/date fields instead of parsing raw API JSON in-house. # Actor input Schema ## `startUrls` (type: `array`): Pages to export. ## `maxItems` (type: `integer`): Stop after this many records. ## Actor input object example ```json { "startUrls": [ { "url": "https://api.crossref.org/works?rows=50" }, { "url": "https://api.crossref.org/journals?rows=50" }, { "url": "https://api.crossref.org/members?rows=50" } ], "maxItems": 50 } ``` # Actor output Schema ## `results` (type: `string`): One structured record per input URL. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://api.crossref.org/works?rows=50" }, { "url": "https://api.crossref.org/journals?rows=50" }, { "url": "https://api.crossref.org/members?rows=50" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("ahmdshrif/crossref-publications-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [ { "url": "https://api.crossref.org/works?rows=50" }, { "url": "https://api.crossref.org/journals?rows=50" }, { "url": "https://api.crossref.org/members?rows=50" }, ] } # Run the Actor and wait for it to finish run = client.actor("ahmdshrif/crossref-publications-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 '{ "startUrls": [ { "url": "https://api.crossref.org/works?rows=50" }, { "url": "https://api.crossref.org/journals?rows=50" }, { "url": "https://api.crossref.org/members?rows=50" } ] }' | apify call ahmdshrif/crossref-publications-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,ahmdshrif/crossref-publications-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 ` 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/mjx4Y1iFNK1cHpvGg/builds/Y2YcSIMiiJEJ1BjVv/openapi.json