# Crossref DOI Metadata Scraper (`parseforge/crossref-scraper`) Actor

Scrapes Crossref publication metadata by search query, title, author, or specific DOI. Returns each work as a flat row with title, authors, container, publication date, and DOI.

- **URL**: https://apify.com/parseforge/crossref-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Other, Education, Automation
- **Stats:** 7 total users, 1 monthly users, 87.5% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $7.00 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)](https://apify.com/parseforge?fpr=vmoqkp)

### Crossref DOI Metadata Scraper

**Scrape Crossref DOI metadata for any publication, search query, or single DOI, up to a million works per run.** Every record comes with its title, authors, container, publication date, and DOI. No API key. Export to CSV, JSON, Excel, or XML.

Crossref's official API is free but rate-limited and returns deeply nested JSON that is painful to flatten. This Actor queries the public REST API directly, applies your filters as it reads, and returns each matching work as one flat row. Search by title, author, free text, or a specific DOI, and collect up to a million records per run.

| Who uses it | What they scrape Crossref for |
|---|---|
| Academic researchers | Building a literature review dataset for a specific topic |
| Librarians | Enriching a catalog with complete DOI metadata |
| Data analysts | Tracking publication output by author or institution |
| Journal editors | Monitoring citations and metadata for their journal |

### What it does

This Actor collects Crossref publication metadata by search query, title, author, or specific DOI, and returns each work as a flat row.

- 🔎 **Search by free text:** query across titles, authors, container titles, and more.
- 📚 **Filter by title or author:** narrow results to exact title or author name matches.
- 🎯 **Fetch a single DOI:** retrieve complete metadata for one known DOI, overriding any query.
- ⚙️ **Crossref filter string:** pass raw filter parameters like type, from-pub-date, or has-orcid.
- 📧 **Polite pool email:** provide a contact email to get faster, more reliable responses from Crossref.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### What you can do with Crossref data

**📖 Build a literature review dataset.**

A PhD student searches for 'attention is all you need' and collects 500 matching works with titles, authors, and publication dates to seed their bibliography.

**🔍 Enrich a catalog with DOI metadata.**

A librarian runs the Actor with a list of DOIs to fill missing title, author, and container fields in their institutional repository.

**📊 Track an author's publication output.**

A research analyst queries by author name and filters by from-pub-date to compile a yearly publication list for a faculty review.

**📈 Monitor journal citations.**

A journal editor uses the filter string 'type:journal-article,container-title:Nature' to collect recent articles and analyze citation patterns.

### Why choose this scraper

|  | What you get |
|---|---|
| **No API key** | Uses Crossref's public REST API, no registration required |
| **Flat output** | Nested JSON is flattened into one row per work |
| **Up to 1M records** | Collect up to a million works per run |
| **Polite pool** | Optional email puts you in Crossref's faster queue |

### How it compares

No other Store actor targets Crossref the same way, so the honest comparison is with the alternatives teams actually weigh.

| | Crossref DOI Metadata Scraper | Build it in-house | By hand |
|---|---|---|---|
| Setup | Run it now, zero config | Days of engineering | None, but hours per pull |
| When Crossref changes | Maintained for you | You fix it | You re-learn the page |
| Proxies, retries, anti-bot | Built in | Your problem | Browser only |
| Output | Fixed JSON schema, CSV/Excel export | Whatever you build | Copy-paste |
| Cost | Pay per result | Engineering time | Analyst hours |

### Configure the run

Drive the Actor from a free text query, a title, an author name, or a specific DOI, and filters run as each work is read so only matches reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

```json
{
  "maxItems": 10,
  "query": "attention is all you need"
}
```

A larger pull:

```json
{
  "maxItems": 200,
  "query": "attention is all you need"
}
```

### Pricing

Pay-per-result: **$0.08 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $8.00 |
| 1,000 results | $80.00 |
| 10,000 results | $800.00 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [Crossref DOI Metadata Scraper](https://apify.com/parseforge/crossref-scraper?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent live access to Crossref through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=parseforge/crossref-scraper"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Check your query for typos or overly restrictive filters. Try a broader search term or remove the filter string. Also ensure you are not using a specific DOI that does not exist.

**Why is the run slow?**

Crossref rate limits apply. Provide an email in the input to join the polite pool, which allows faster request rates. Reduce maxItems if you only need a sample.

**Why are some fields empty in the output?**

Not all Crossref records have every field. For example, some works may lack an abstract or ORCID. Empty fields are normal for incomplete metadata.

**Why did the run stop before reaching maxItems?**

Crossref may have no more results for your query. Try a different search term or remove filters to see if more records are available.

### FAQ

| Question | Answer |
|---|---|
| Do I need a Crossref API key? | No. This Actor uses Crossref's public REST API, which does not require an API key. Providing an email in the input puts your requests in the polite pool for faster responses. |
| How many records can I collect per run? | You can set maxItems up to 1,000,000. The Actor will stop after collecting that many works or when Crossref has no more results for your query. |
| Can I fetch metadata for a single DOI? | Yes. Enter the DOI in the 'Specific DOI' field and the Actor will return that one work, ignoring any other query parameters. |
| What is the filter string? | It is a raw Crossref filter parameter, such as 'type:journal-article,from-pub-date:2024,has-orcid:true'. You can find the full syntax in the Crossref API documentation. |
| Does the Actor flatten nested metadata? | Yes. Crossref returns deeply nested JSON, but this Actor flattens each work into a single row with fields like title, authors, container title, and publication date. |
| Can I search by author name? | Yes. Use the 'Author name' field to match works by a specific author. You can combine it with other filters. |
| What export formats are supported? | You can export the dataset to CSV, JSON, Excel, or XML from the Apify platform. |
| Is there a rate limit? | Crossref has rate limits on its public API. Providing an email in the polite pool increases your allowed request rate. |
| Can I filter by publication date? | Yes. Use the filter string with 'from-pub-date' or 'until-pub-date' parameters, or include them in your free text query. |
| Does this Actor work with any Crossref content type? | Yes. It returns journal articles, conference papers, books, datasets, and other works indexed by Crossref. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Crossref. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

## `maxItems` (type: `integer`):

How many works to collect per run.

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

Free text query. Crossref searches across titles, authors, container titles, and more.

## `queryTitle` (type: `string`):

Match only within titles.

## `queryAuthor` (type: `string`):

Match by author name.

## `filter` (type: `string`):

Optional Crossref filter (e.g. 'type:journal-article,from-pub-date:2024,has-orcid:true'). See https://api.crossref.org.

## `doi` (type: `string`):

Fetch metadata for a single DOI (overrides query).

## `email` (type: `string`):

Providing an email puts your requests in Crossref's faster 'polite pool'.

## Actor input object example

```json
{
  "maxItems": 10,
  "query": "attention is all you need"
}
```

# Actor output Schema

## `overview` (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 = {
    "maxItems": 10,
    "query": "attention is all you need"
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/crossref-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "maxItems": 10,
    "query": "attention is all you need",
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/crossref-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 '{
  "maxItems": 10,
  "query": "attention is all you need"
}' |
apify call parseforge/crossref-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/crossref-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 <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/bgepRP8yugrDefI38/builds/vK5ZJh8Lx4BTvixi5/openapi.json