# Academic Paper Search: Crossref & PubMed Metadata (`lepidata/academic-papers`) Actor

Search Crossref and PubMed in one run and get clean paper metadata and links: title, authors, DOI, PMID, venue, date. No full text and no API key.

- **URL**: https://apify.com/lepidata/academic-papers.md
- **Developed by:** [Lepi Data](https://apify.com/lepidata) (community)
- **Categories:** Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.10 / 1,000 paper results

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

## Academic Paper Search: Crossref & PubMed Metadata

**What it does.** Runs one keyword search across free official scholarly databases and returns one row per paper per source, with metadata and links only. **Crossref and PubMed are live. arXiv support is coming soon and will turn on when enabled.** Until then, selecting arXiv returns one free `service-busy` row, and the other sources still run normally.

**Input** (from `.actor/input_schema.json`)

- `query` (required): keywords to search in paper metadata
- `sources`: any of `crossref`, `pubmed`, `arxiv`. Default `["crossref","pubmed"]`.
- `maxResultsPerSource`: 1–1000, default 20. Maximum papers returned and charged from each source.

**Output fields**
`type`, `source`, `title`, `authors` (as published), `published`, `venue`, `publisher` (Crossref), `doi`, `pmid`, `pmcid`, `arxivId`, `categories` (arXiv), `citedByCount` (Crossref), `url` (landing page), `pdfUrl` (link only, where the source lists one)
Free status rows (not charged): `no-results`, `service-busy`, `source-error`, `invalid-input`, `free-plan-limit`, `charge-limit-reached`, each with `errorCode`/message.

**Example**
Input: `{"query":"large language models","sources":["crossref","pubmed"],"maxResultsPerSource":10}`
Output row (illustrative shape): `{"type":"paper","source":"crossref","title":"…","authors":["A. Author","B. Author"],"published":"2026-…","venue":"…","publisher":"…","doi":"10.…","citedByCount":…,"url":"https://doi.org/10.…"}`

**Data source and compliance**

- Data comes only from the Crossref REST API and NCBI E-utilities (PubMed), plus the arXiv API when it's enabled. No keys, and requests can only go to those hosts.
- **Metadata and links only. No abstracts, full text or PDFs are downloaded or returned.** Copyright stays with publishers and authors.
- When arXiv is enabled, it will be limited to one shared request every 3 seconds across all users, per arXiv's API terms, so arXiv results will be slower. PubMed stays at or under 3 requests per second.
- If a source is busy or unavailable, you get a free `service-busy` or `source-error` row and are not charged for that source.
- Free-plan accounts get up to 100 results per run.

**Pricing.** Pay per result: $0.10 per 1,000 papers, flat on every plan, no start fee. Free status rows are never charged.

# Actor input Schema

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

Keywords to search for in paper metadata.

## `sources` (type: `array`):

Which official databases to search. arXiv is shared-rate-limited (1 request / 3 s for all users), so it is slower.

## `maxResultsPerSource` (type: `integer`):

Maximum papers returned (and charged) from each source.

## Actor input object example

```json
{
  "query": "large language models",
  "sources": [
    "crossref",
    "pubmed"
  ],
  "maxResultsPerSource": 10
}
```

# Actor output Schema

## `items` (type: `string`):

All rows from this run.

# 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 = {
    "query": "large language models",
    "sources": [
        "crossref",
        "pubmed"
    ],
    "maxResultsPerSource": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("lepidata/academic-papers").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 = {
    "query": "large language models",
    "sources": [
        "crossref",
        "pubmed",
    ],
    "maxResultsPerSource": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("lepidata/academic-papers").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 '{
  "query": "large language models",
  "sources": [
    "crossref",
    "pubmed"
  ],
  "maxResultsPerSource": 10
}' |
apify call lepidata/academic-papers --silent --output-dataset

```

## MCP server setup

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

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/xvNtq02OX2sXu4cdK/builds/fHcpiiAJmrkqXBI1j/openapi.json