# Crossref DOI & Paper Metadata API: Citations, Journals (`catblik/crossref-works`) Actor

Look up scholarly papers by DOI or keyword using the official Crossref API: title, authors, journal, date, citation count, license and abstract.

- **URL**: https://apify.com/catblik/crossref-works.md
- **Developed by:** [asaf meizner](https://apify.com/catblik) (community)
- **Categories:** Education, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 work record returneds

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

## Crossref DOI & Paper Metadata API

Turn DOIs or keywords into clean scholarly metadata using the **official Crossref REST API** (open bibliographic data, no login, no scraping). Each row has title, authors (names only), journal, publisher, publication date, volume/issue/pages, citation count, reference count, license link, subjects and abstract when Crossref has it.

### Use cases

- Enrich a reference list or spreadsheet of DOIs.
- Find the most cited papers on a topic since a given year.
- Check citation counts for a set of papers over time (schedule a run).
- Feed bibliographic data to research or RAG pipelines.

### Input

```json
{ "dois": ["10.1038/nature12373", "https://doi.org/10.1126/science.169.3946.635"] }
```

or a keyword search:

```json
{ "query": "graph neural networks", "maxResults": 50, "fromPubDate": "2022", "sortByCitations": true }
```

`contactEmail` is optional: it is sent in the User-Agent so Crossref can contact you (their "polite pool").

### Output

```json
{ "doi": "10.1038/nature12373", "status": "ok", "title": "...", "type": "journal-article",
  "authors": ["..."], "journal": "Nature", "publishedDate": "2013-07", "citedByCount": 1234 }
```

DOIs that do not exist return `{"status": "not_found"}` and are not charged.

### Pricing

Pay per event: **$0.002 per work record returned** (about $2 per 1,000). Not-found rows are free.

### Notes

Sequential requests at about one per second with an identifying User-Agent; stops on repeated errors. Abstracts are only present when the publisher deposited them. Coverage and citation counts are those of Crossref, which differ from Google Scholar or Scopus.

Keyword searches use Crossref’s broad relevance matching; results may not contain every search word. Check titles and abstracts before using them as a topic-specific research set.

# Actor input Schema

## `dois` (type: `array`):

Up to 500 DOIs, plain or as doi.org links.

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

Optional. Search papers by title, author or topic words.

## `maxResults` (type: `integer`):

Maximum papers returned by the keyword search.

## `fromPubDate` (type: `string`):

Optional, YYYY or YYYY-MM-DD, applies to keyword search.

## `sortByCitations` (type: `boolean`):

Sort keyword search results by citation count.

## `contactEmail` (type: `string`):

Sent to Crossref in the User-Agent so they can reach you; it puts requests in their faster 'polite' pool.

## Actor input object example

```json
{
  "dois": [
    "10.1038/nature12373"
  ],
  "maxResults": 20,
  "sortByCitations": false
}
```

# 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("catblik/crossref-works").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("catblik/crossref-works").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 catblik/crossref-works --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,catblik/crossref-works"
        }
    }
}
```

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/LB7uPByduGEMUxhqW/builds/UcnMVYG114mTzprH3/openapi.json