# PubMed Article Scraper - Medical Research Extractor (`klondikeking/pubmed-articles-scraper`) Actor - **URL**: https://apify.com/klondikeking/pubmed-articles-scraper.md - **Developed by:** [Pierrick McD0nald](https://apify.com/klondikeking) (community) - **Categories:** Developer tools, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 Article Scraper — Medical Research & Paper Metadata Extractor Extract medical and life sciences research article metadata from PubMed using the official NCBI E-utilities API. This Actor retrieves titles, authors, journal names, publication dates, DOIs, and optional abstracts for any PubMed search query — no scraping required, no proxy costs, 100% reliable. ### Use Cases - **Systematic Literature Reviews** — Collect article metadata for meta-analysis and review papers - **Research Trend Analysis** — Track publication trends in specific medical fields over time - **Citation Mining** — Build datasets of relevant papers for bibliometric analysis - **Drug & Disease Monitoring** — Stay updated on latest research for specific conditions or treatments - **Academic Research** — Gather structured publication data for machine learning or NLP projects ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `searchQuery` | String | Yes | Search terms to query PubMed (e.g., "machine learning diabetes") | | `maxResults` | Number | No | Maximum articles to extract, 1–1000 (default: 100) | | `sort` | String | No | Sort by `relevance` or `pubDate` (default: relevance) | | `dateRange` | String | No | Filter by year range, e.g. `2020:2025` or `2024` | | `includeAbstract` | Boolean | No | Fetch article abstracts (slower, extra API calls) | | `proxyConfiguration` | Object | No | Proxy configuration (not required for NCBI API) | ### Output The Actor outputs a dataset with the following fields: ```json { "pmid": "42117144", "title": "Cardiovascular Risk Stratification in Youth-Onset Type 2 Diabetes Using Machine Learning.", "authors": ["Joo EY", "Lee YS", "Shin EJ", "Kim SJ", "Lee JE"], "journal": "J Korean Med Sci", "pubDate": "2026 May 11", "volume": "41", "issue": "18", "pages": "e4", "doi": "10.3346/jkms.2026.41.e4", "language": "eng", "abstract": "", "pubTypes": ["Journal Article"] } ```` ### Pricing Pay per event: **$0.001 per article extracted** (minimum charge applies). NCBI E-utilities is a free public API with no proxy or scraping costs, giving this Actor margins above 95%. ### Limitations - Abstract fetching requires additional API calls and is slower - NCBI rate limits: ~3 requests/second without an API key - Very large result sets (>1000) require multiple search strategies - Some older articles may have incomplete metadata ### FAQ **Q: Do I need an NCBI API key?** A: No. This Actor works with the public E-utilities API. An API key increases rate limits but is not required. **Q: Can I search by author or journal?** A: Yes. Use PubMed search syntax in `searchQuery`, e.g., `Smith J[Author] AND Nature[Journal]`. **Q: Why are some abstracts empty?** A: Not all PubMed records include abstracts. Enable `includeAbstract` to attempt fetching them. ### Changelog - **v1.0.0** — Initial release with search, metadata extraction, and optional abstract fetching # Actor input Schema ## `searchQuery` (type: `string`): Search terms to query PubMed (e.g., 'machine learning diabetes') ## `maxResults` (type: `integer`): Maximum number of articles to extract (1-1000) ## `sort` (type: `string`): How to sort the results ## `dateRange` (type: `string`): Filter by publication year range (e.g., '2020:2025' or '2024') ## `includeAbstract` (type: `boolean`): Fetch article abstracts (slower, requires additional API calls) ## `proxyConfiguration` (type: `object`): Configure proxy settings for the Actor ## Actor input object example ```json { "searchQuery": "machine learning", "maxResults": 100, "sort": "relevance", "includeAbstract": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): No description ## `stats` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQuery": "machine learning", "maxResults": 100, "sort": "relevance", "dateRange": "", "includeAbstract": false, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("klondikeking/pubmed-articles-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQuery": "machine learning", "maxResults": 100, "sort": "relevance", "dateRange": "", "includeAbstract": False, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("klondikeking/pubmed-articles-scraper").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 '{ "searchQuery": "machine learning", "maxResults": 100, "sort": "relevance", "dateRange": "", "includeAbstract": false, "proxyConfiguration": { "useApifyProxy": true } }' | apify call klondikeking/pubmed-articles-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=klondikeking/pubmed-articles-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PubMed Article Scraper - Medical Research Extractor", "version": "1.0", "x-build-id": "kn6hH79SlYaa8m9av" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/klondikeking~pubmed-articles-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-klondikeking-pubmed-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/klondikeking~pubmed-articles-scraper/runs": { "post": { "operationId": "runs-sync-klondikeking-pubmed-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/klondikeking~pubmed-articles-scraper/run-sync": { "post": { "operationId": "run-sync-klondikeking-pubmed-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchQuery" ], "properties": { "searchQuery": { "title": "Search Query", "minLength": 1, "type": "string", "description": "Search terms to query PubMed (e.g., 'machine learning diabetes')" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of articles to extract (1-1000)", "default": 100 }, "sort": { "title": "Sort By", "enum": [ "relevance", "pubDate" ], "type": "string", "description": "How to sort the results", "default": "relevance" }, "dateRange": { "title": "Date Range Filter", "type": "string", "description": "Filter by publication year range (e.g., '2020:2025' or '2024')" }, "includeAbstract": { "title": "Include Abstracts", "type": "boolean", "description": "Fetch article abstracts (slower, requires additional API calls)", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Configure proxy settings for the Actor" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```