# PubMed Scraper — Biomedical Research Papers (`du7chmaniac/pubmed-scraper`) Actor Scrape biomedical research papers from PubMed via the NCBI E-utilities API. Search by keyword with optional date range, retrieve article metadata, abstracts, authors, MeSH terms, and DOIs. Supports both summary (fast) and full (with abstract) retrieval modes. - **URL**: https://apify.com/du7chmaniac/pubmed-scraper.md - **Developed by:** [Joren Maurissen](https://apify.com/du7chmaniac) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 Scraper — Biomedical Research Papers Search and scrape biomedical research papers from [PubMed](https://pubmed.ncbi.nlm.nih.gov/) using the NCBI E-utilities API. No API key required — the NCBI E-utilities are free and open. ### Features - **Keyword search** with PubMed query syntax support (e.g. `CRISPR gene editing`, `cancer AND immunotherapy`) - **Two retrieval modes**: - **Summary** (fast): title, authors, journal, publication date, DOI, pub type, language - **Full** (detailed): everything in summary + abstract, MeSH terms, ISSN, publication year - **Date range filtering** (e.g. `2020:2026`) to narrow results by publication date - **Sort by relevance or date** — use PubMed's native ranking or get the most recent papers - **Structured output** — clean JSON records ready for analysis, with PubMed URLs for each article - **Rate-limit aware** — respects NCBI's 3 requests/second guideline ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `searchTerm` | string | ✅ | `cancer` | PubMed search query (supports full PubMed syntax) | | `maxResults` | integer | | `20` | Maximum articles to retrieve (1–10,000) | | `retType` | select | | `summary` | `summary` (fast) or `full` (with abstracts + MeSH terms) | | `sort` | select | | `relevance` | `relevance` or `date` (most recent first) | | `dateRange` | string | | — | Publication date range, e.g. `2020:2026` | ### Output Each article is pushed as a JSON record to the dataset: #### Summary mode fields | Field | Description | |-------|-------------| | `pmid` | PubMed Unique Identifier | | `title` | Article title | | `authors` | Author names (semicolon-separated) | | `journal` | Journal abbreviation/source | | `pubDate` | Publication date | | `epubDate` | Electronic publication date | | `doi` | Digital Object Identifier | | `pubType` | Publication type(s) | | `lang` | Language(s) | | `url` | PubMed URL for the article | | `scrapedAt` | ISO timestamp of scrape | #### Full mode adds | Field | Description | |-------|-------------| | `abstract` | Full abstract text | | `issn` | ISSN | | `pubYear` | Publication year | | `meshTerms` | MeSH subject headings (semicolon-separated) | ### Example Input ```json { "searchTerm": "CRISPR gene editing", "maxResults": 50, "retType": "full", "sort": "date", "dateRange": "2023:2026" } ```` ### Use Cases - **Literature reviews** — batch-download article metadata for systematic reviews - **Research monitoring** — track new publications in your field by date range - **Bibliometric analysis** — extract author lists, MeSH terms, and publication patterns - **Data enrichment** — get DOIs and PubMed URLs for reference management - **AI/ML training data** — build datasets of biomedical abstracts for NLP tasks ### Technical Details This actor uses the [NCBI E-utilities API](https://www.ncbi.nlm.nih.gov/books/NBK25500/): - **esearch.fcgi** — searches PubMed and returns PMIDs - **esummary.fcgi** — fetches document summaries (summary mode) - **efetch.fcgi** — fetches full XML records parsed with BeautifulSoup (full mode) No authentication required. The actor respects NCBI's rate limit guideline (≤3 requests/second). ### Pricing Pay per result — you only pay for the articles actually returned in the dataset. # Actor input Schema ## `searchTerm` (type: `string`): PubMed search query (supports PubMed search syntax, e.g. 'CRISPR gene editing', 'cancer AND immunotherapy'). ## `maxResults` (type: `integer`): Maximum number of articles to retrieve. ## `retType` (type: `string`): summary = fast document summaries (title, authors, journal, DOI); full = complete records with abstracts and MeSH terms (slower). ## `sort` (type: `string`): Sort order for search results: relevance (default PubMed relevance) or date (most recent first). ## `dateRange` (type: `string`): Optional publication date range, e.g. '2020:2026'. Filters by publication date. ## `proxyConfiguration` (type: `object`): Optional — NCBI limits 3 req/sec per IP without API key ## Actor input object example ```json { "searchTerm": "cancer", "maxResults": 20, "retType": "summary", "sort": "relevance", "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "searchTerm": "cancer", "dateRange": "" }; // Run the Actor and wait for it to finish const run = await client.actor("du7chmaniac/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchTerm": "cancer", "dateRange": "", } # Run the Actor and wait for it to finish run = client.actor("du7chmaniac/pubmed-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 '{ "searchTerm": "cancer", "dateRange": "" }' | apify call du7chmaniac/pubmed-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=du7chmaniac/pubmed-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PubMed Scraper — Biomedical Research Papers", "description": "Scrape biomedical research papers from PubMed via the NCBI E-utilities API. Search by keyword with optional date range, retrieve article metadata, abstracts, authors, MeSH terms, and DOIs. Supports both summary (fast) and full (with abstract) retrieval modes.", "version": "0.1", "x-build-id": "FUYfSmx22pDiStwTv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/du7chmaniac~pubmed-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-du7chmaniac-pubmed-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/du7chmaniac~pubmed-scraper/runs": { "post": { "operationId": "runs-sync-du7chmaniac-pubmed-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/du7chmaniac~pubmed-scraper/run-sync": { "post": { "operationId": "run-sync-du7chmaniac-pubmed-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchTerm" ], "properties": { "searchTerm": { "title": "Search term", "type": "string", "description": "PubMed search query (supports PubMed search syntax, e.g. 'CRISPR gene editing', 'cancer AND immunotherapy')." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of articles to retrieve.", "default": 20 }, "retType": { "title": "Retrieval type", "enum": [ "summary", "full" ], "type": "string", "description": "summary = fast document summaries (title, authors, journal, DOI); full = complete records with abstracts and MeSH terms (slower).", "default": "summary" }, "sort": { "title": "Sort order", "enum": [ "relevance", "date" ], "type": "string", "description": "Sort order for search results: relevance (default PubMed relevance) or date (most recent first).", "default": "relevance" }, "dateRange": { "title": "Date range (YYYY:YYYY)", "type": "string", "description": "Optional publication date range, e.g. '2020:2026'. Filters by publication date." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional — NCBI limits 3 req/sec per IP without API key", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```