Crossref Recent Publications by Query

For each query, pull recently-published works from Crossref's public DOI registry. One row per work, with a server-side date filter so even narrow daily windows are fast.

What you get

{
  "doi":           "10.1145/3674892.3675012",
  "title":         "Differentially Private In-Context Learning",
  "type":          "proceedings-article",
  "publisher":     "Association for Computing Machinery",
  "container":     "Proceedings of the 31st ACM SIGKDD Conference",
  "shortContainer":"KDD '26",
  "issn":          ["2153-1234"],
  "authors":       ["Alice Doe", "Bob Smith"],
  "authorCount":   2,
  "published":     "2026-05-30",
  "created":       "2026-06-01",
  "abstract":      "We study DP-SGD applied to ICL...",
  "subject":       ["Computer Science"],
  "referenceCount":     42,
  "isReferencedByCount":  0,
  "licenseUrl":    "https://www.acm.org/publications/policies/...",
  "funders":       ["NSF", "DARPA"],
  "url":           "https://doi.org/10.1145/3674892.3675012",
  "query":         "differential privacy"
}

Why this matters

PubMed covers biomedical only. arXiv covers preprints in physics, CS, math, q-bio only. Crossref covers everything else (humanities, social sciences, business, law, ecology, materials science) wherever a DOI is registered. A single query gets you the new-works feed across all of academia.

How to use

Input. A list of search queries plus a date window in days. The date filter runs server-side (no over-fetch), so a 1-day window costs only as much compute as a 1-day window.

{
  "queries": ["climate change adaptation", "battery recycling"],
  "sinceDays": 7,
  "dateField": "published",
  "maxResultsPerQuery": 1000,
  "typesFilter": []
}

dateField.

• published (default): filter on the work's print or online publication date. Best for "what came out this week."
• created: filter on when Crossref first indexed the work. Useful when a publisher backdates the print date but the DOI is fresh.

typesFilter. Restrict to specific Crossref work types. Common values: journal-article, book-chapter, proceedings-article, posted-content, dataset. Empty = no filter.

Pricing

Pay per event. Price per 1,000 events:

Event	Base price	Bronze	Silver	Gold
Crossref publication extracted	$0.20	$0.18	$0.16	$0.14

Bronze, Silver and Gold are the discounts Apify gives users of its paid plans. The Pricing tab always shows the current prices.

Buyer

• Academic research offices (literature scans).
• Bibliometrics / research-impact tools.
• Patent firms (prior-art sweep).
• Journalists tracking new policy / health / climate publications.
• Anyone building a literature-review tool that needs a working daily new-works feed.

Run it through the API

Python, with the apify-client package:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("v0iddo/crossref-recent-publications").call(run_input={"queries": ["climate change adaptation", "battery recycling"], "maxResultsPerQuery": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript, with the apify-client package:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('v0iddo/crossref-recent-publications').call({"queries": ["climate change adaptation", "battery recycling"], "maxResultsPerQuery": 20});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call that waits for the run and returns the rows (for runs that finish within 5 minutes):

curl -X POST "https://api.apify.com/v2/acts/v0iddo~crossref-recent-publications/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"queries": ["climate change adaptation", "battery recycling"], "maxResultsPerQuery": 20}'

Use it from an agent (MCP)

Claude, Cursor, VS Code and other MCP clients can call this actor as a tool through the Apify MCP server. Add it to the client's MCP configuration:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=v0iddo/crossref-recent-publications",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

FAQ

Do I need an account, cookies or an API key?

No. The actor reads public data without logging in. You only need an Apify account to start it.

How many results can one run return?

Set Max results per query (up to 100,000) to the number you need. Large jobs can also be split into several runs or scheduled.

How am I charged?

Pay per event, at the prices on the Pricing tab for your Apify plan (the Pricing section of this page lists them). The platform usage of the run is included in those prices, and your spending limit for a run is always respected.

Why did my run return no results?

The status message and the log of the run say why: usually nothing matched the input, or the source did not answer for a moment. Check the input against the example above and run it again.

Can I run it on a schedule?

Yes. Save your input as a task and add a schedule in the Apify Console (daily, hourly or with a cron expression). Each run gets its own dataset, so you keep a history.

Which formats can I export?

JSON, CSV, Excel, XML, HTML table and RSS from the Output tab or the API. Integrations send the rows to Google Sheets, Slack, Make, Zapier, n8n or a webhook.

Is collecting this data allowed?

The actor collects data that the source publishes openly, without a login. Public data can still be personal data under laws such as the GDPR, and sources have their own terms: make sure your use of the data follows the rules that apply to you.

What happens when the source changes?

An automated test runs the actor every day on the example input and checks the rows, not only that the run finished. When a check fails, the actor is repaired and rebuilt; the build history on this page shows each update.

Something is missing or wrong. Where do I report it?

Open an issue on the Issues tab of this actor with the run link. Requests for a new field are welcome too.

Related actors

• NIH RePORTER Scraper: Research Grants by Query
• News Article Extractor: Full Text from Links and RSS
• Substack Posts Scraper: Archive, Reactions, Comments
• Hacker News Scraper: Stories and Comments by Query

Source

https://api.crossref.org/works: Crossref's public REST API. The actor pages with the cursor=* deep-pagination protocol so even 100 000-result windows finish without state. UA includes a polite mailto: to land on the prioritized API pool.