# PubMed Biomedical Article Search (`fit_melon/pubmed-biomedical-article-search`) Actor

Search PubMed's 35M+ biomedical citations by keyword: title, authors, journal, year, DOI, PMID and abstract for each match. Official NCBI E-utilities API. Free — you only pay Apify usage.

- **URL**: https://apify.com/fit\_melon/pubmed-biomedical-article-search.md
- **Developed by:** [D N](https://apify.com/fit_melon) (community)
- **Categories:** AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## 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

## PubMed Biomedical Article Search — Free

Search **PubMed** — the U.S. National Library of Medicine's database of 35M+ biomedical and life-science citations — by keyword and get clean, structured results: title, authors, journal, publication date, volume/issue/pages, DOI, PMID and article URL. Powered by the official [NCBI E-utilities](https://www.ncbi.nlm.nih.gov/books/NBK25501/) API.

This actor is **free** — you only pay for your own Apify platform usage.

### What it does

Give it one or more search queries (PubMed syntax supported) and a per-query result limit; it returns one structured record per matching article, plus explicit `not_found` / `error` rows so nothing fails silently. Ideal for literature reviews, systematic-review pipelines, research monitoring and citation enrichment.

### Input

| Field | Type | Description |
|---|---|---|
| `queries` | array of strings | PubMed search terms (query syntax supported). |
| `maxResultsPerQuery` | integer | Top articles per query (1-50). Default `10`. |

### Output (example)

```json
{
  "query": "crispr gene editing",
  "status": "found",
  "pmid": "42413101",
  "title": "CRISPR-Cas systems for genome editing ...",
  "authors": ["Doe J", "Smith A"],
  "journal": "Nature Biotechnology",
  "pubdate": "2025 Jun",
  "doi": "10.1038/s41587-025-xxxxx",
  "url": "https://pubmed.ncbi.nlm.nih.gov/42413101/"
}
```

### Use cases

- Automate literature reviews and research monitoring.
- Build systematic-review or meta-analysis pipelines.
- Enrich a reference manager with DOIs and metadata.
- Track new publications on a topic on a schedule.

### Limitations & fair use

Uses NCBI E-utilities with a proper User-Agent and polite throttling (≤3 requests/second, as recommended for unauthenticated use). Abstracts and full text are subject to publisher terms; this actor returns citation metadata. Please follow NCBI's usage guidelines.

### More actors by this developer

See the full range of free actors on the [fit\_melon profile](https://apify.com/fit_melon).

# Actor input Schema

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

PubMed search terms (supports PubMed query syntax, e.g. "crispr", "covid-19 vaccine efficacy"). One block of results per query.

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

How many top articles to return per query (1-50).

## Actor input object example

```json
{
  "queries": [
    "crispr gene editing",
    "alzheimer biomarkers"
  ],
  "maxResultsPerQuery": 10
}
```

# 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 gene editing",
        "alzheimer biomarkers"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("fit_melon/pubmed-biomedical-article-search").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 gene editing",
        "alzheimer biomarkers",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("fit_melon/pubmed-biomedical-article-search").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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 gene editing",
    "alzheimer biomarkers"
  ]
}' |
apify call fit_melon/pubmed-biomedical-article-search --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=fit_melon/pubmed-biomedical-article-search",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3S74nd6J6tOqzhT8C/builds/XTEaWcG5fTyy1Ojf5/openapi.json