# 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 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 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 '' with your token const client = new ApifyClient({ 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 '' with your token. client = ApifyClient("") # 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 " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PubMed Biomedical Article Search", "description": "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.", "version": "0.0", "x-build-id": "XTEaWcG5fTyy1Ojf5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fit_melon~pubmed-biomedical-article-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fit_melon-pubmed-biomedical-article-search", "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/fit_melon~pubmed-biomedical-article-search/runs": { "post": { "operationId": "runs-sync-fit_melon-pubmed-biomedical-article-search", "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/fit_melon~pubmed-biomedical-article-search/run-sync": { "post": { "operationId": "run-sync-fit_melon-pubmed-biomedical-article-search", "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": [ "queries" ], "properties": { "queries": { "title": "Search queries", "type": "array", "description": "PubMed search terms (supports PubMed query syntax, e.g. \"crispr\", \"covid-19 vaccine efficacy\"). One block of results per query.", "items": { "type": "string" } }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "maximum": 50, "type": "integer", "description": "How many top articles to return per query (1-50).", "default": 10 } } }, "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 } } } } } } } } } } ```