# PubMed Scraper — Articles, Abstracts, MeSH & DOIs (`northbell/pubmed-scraper`) Actor

Search PubMed with full PubMed query syntax and get each article: title, abstract, journal, publication date, DOI, PMCID, MeSH terms, keywords, publication types, author count and institutions. Filter by date and get only new articles since your last run. Official NCBI API, no key.

- **URL**: https://apify.com/northbell/pubmed-scraper.md
- **Developed by:** [Northbell](https://apify.com/northbell) (community)
- **Categories:** AI, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.80 / 1,000 articles

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?

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

## PubMed Scraper — Articles, Abstracts, MeSH & DOIs

Search **PubMed** exactly the way you do on the website — field tags like `[tiab]`, `[mh]`, `[ta]` and `AND` / `OR` / `NOT` all work — and get each article as a clean row: **title, abstract, journal, publication date, DOI, PMCID, MeSH terms, keywords, publication types, author count and institutions**. Filter by publication date, and schedule it with *Only new articles* to follow a topic week by week.

### What you get

| Field | What it is |
|---|---|
| `pmid`, `url`, `title`, `abstract` | the article (structured abstracts keep their section labels) |
| `journal`, `journalAbbreviation`, `volume`, `issue`, `pages` | where it was published |
| `publicationDate`, `year` | when |
| `doi`, `pmcid` | links to the full text (PMCID = free full text in PubMed Central) |
| `meshTerms`, `keywords`, `publicationTypes`, `language` | indexing — e.g. `Randomized Controlled Trial`, `Review` |
| `authors` | author names in the article's order (first name, last name; or the group name) |
| `authorCount`, `institutions` | how many authors, and their institutions |
| `query`, `isNewSinceLastRun` | which query found it, and whether it is new since your last run |

E-mail addresses are removed from institutions.

### Use it for

- **Literature monitoring** — a weekly list of new papers on your topic, with abstracts, into a sheet or Slack
- **Systematic reviews** — export every match for a query with MeSH terms and publication types for screening
- **AI and RAG** — abstracts with DOIs for summaries, search and evidence tables
- **Research landscaping** — which journals and institutions publish on a topic, by year

### Input

```json
{ "queries": ["glp-1[tiab] AND (obesity[mh] OR weight loss[tiab])"], "fromDate": "2025", "maxResultsPerQuery": 200, "onlyNew": true }
```

Measured on October 7, 2026: two queries, 54 articles with abstracts in 6 seconds. Data comes from NCBI's official E-utilities API — no login, no API key; requests are paced to NCBI's limit of three a second.

### Pricing

**$1.00 per 1,000 articles**, plus $0.01 per run. Error rows are free. The $0.01 run-start fee is the one charge every run pays, even one that returns nothing.

### For AI agents

`{"queries": ["long covid[tiab]"], "maxResultsPerQuery": 20}` returns the 20 newest articles with abstracts. Rows have `type`: `article` or `error`.

# Actor input Schema

## `queries` (type: `array`):

Anything you would type in PubMed, including field tags (\[tiab], \[mh], \[au], \[ta]) and AND / OR / NOT.

## `pmids` (type: `array`):

PubMed IDs or pubmed.ncbi.nlm.nih.gov links to fetch directly.

## `fromDate` (type: `string`):

e.g. "2024" or "2024-06-01".

## `toDate` (type: `string`):

Keep articles published up to this date. Write 2025, 2025-12 or 2025-12-31. Leave empty for no end date.

## `sort` (type: `string`):

Newest first, or PubMed's best match order.

## `maxResultsPerQuery` (type: `integer`):

How many articles to return for each query. PubMed returns at most 9,999 per query.

## `includeAbstract` (type: `boolean`):

Add the abstract text to each article.

## `onlyNew` (type: `boolean`):

From the second run on, return only articles this Actor has not returned before for the same query. Schedule it to follow a topic.

## Actor input object example

```json
{
  "queries": [
    "crispr[tiab] AND cancer[mh]"
  ],
  "sort": "pub_date",
  "maxResultsPerQuery": 100,
  "includeAbstract": true,
  "onlyNew": false
}
```

# Actor output Schema

## `articles` (type: `string`):

Articles with abstract, journal, date, DOI and MeSH terms.

# 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 = {
    "queries": [
        "crispr[tiab] AND cancer[mh]"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("northbell/pubmed-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 = { "queries": ["crispr[tiab] AND cancer[mh]"] }

# Run the Actor and wait for it to finish
run = client.actor("northbell/pubmed-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 '{
  "queries": [
    "crispr[tiab] AND cancer[mh]"
  ]
}' |
apify call northbell/pubmed-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,northbell/pubmed-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/eVxbPhrfFN6e653rc/builds/SMHh0O6LcVppKLiNe/openapi.json