# Research Paper Alerts: PubMed, Europe PMC and OpenAlex Watch (`accountable_eel/research-literature-watch`) Actor New research papers and preprints for your keywords from PubMed, Europe PMC, bioRxiv, medRxiv and OpenAlex, one de-duplicated row per paper, with a monitoring mode that only returns and bills papers new since your last run. - **URL**: https://apify.com/accountable_eel/research-literature-watch.md - **Developed by:** [Adriana Voss](https://apify.com/accountable_eel) (community) - **Categories:** Developer tools, Education - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 paper returneds 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 ## Research Paper Alerts: PubMed, Europe PMC and OpenAlex Watch **Get the new research papers and preprints for your keywords, one clean row per paper, from PubMed, Europe PMC, bioRxiv, medRxiv, arXiv and OpenAlex in a single run.** Each watch query is searched in two open indexes: Europe PMC, which carries PubMed, PubMed Central and life-science preprints, and OpenAlex, which adds arXiv and every other field. A paper that both indexes hold comes back once, with its DOI, PubMed ID, abstract, journal or preprint server, a free full-text link when one exists, and the list of places it was found. Turn on monitoring and put the run on a schedule to get only the papers that are new since your last run, charged per paper and free on a quiet day. **Who uses it:** researchers and lab managers who want a keyword alert without five separate email digests, biotech business-development and competitive-intelligence teams tracking a target, a drug or a method, medical-affairs and pharmacovigilance teams watching a compound, and builders who feed new abstracts to a summariser or a Slack channel. **Related actors:** for a one-off literature search with citation counts and author affiliations use [OpenAlex Work Search](https://apify.com/accountable_eel/openalex-work-search-lookup); to resolve a list of DOIs use [Crossref DOI Lookup](https://apify.com/accountable_eel/crossref-doi-lookup). This actor is the alert: newest first, de-duplicated, with a memory. ### How to use 1. **In the Apify Console.** Open the actor page and click **Start** — the `queries` field is already pre-filled with a working example. Results land in the run's dataset as soon as each item is found. 2. **Via the API.** Call it directly with a POST request — no Console needed once you have an API token: ```bash curl "https://api.apify.com/v2/acts/accountable_eel~research-literature-watch/run-sync-get-dataset-items?token=" \ -X POST \ -H "Content-Type: application/json" \ -d '{"queries":["llm"]}' ``` 3. **On a schedule.** Save this actor as an Apify **Task** with the input you want, then add a **Schedule** (hourly, daily, weekly) so it runs on its own — no server of your own required. ### Input ```json { "queries": [ "llm" ] } ``` One watch per line, up to 20. Plain words are all required (CRISPR base editing); put a phrase in quotes ("large language model"); AND, OR, NOT and parentheses work. Each line is its own watch with its own memory. Accepted formats: llm, "large language model" AND radiology, CRISPR base editing, (semaglutide OR tirzepatide) AND obesity. Each line of `queries` is its own watch. Words are matched in the title and abstract by default, which keeps an alert on topic; switch `matchIn` to the full text for a broad sweep. `sinceDays` (default 30) is the publication window and `maxItems` (default 25, up to 100) caps the papers per query, newest first. Include and exclude keywords are applied before anything is remembered or charged. Uploads to general-purpose repositories (Zenodo, figshare, Kaggle) are left out: on a keyword they are mostly datasets, slides and self-published notes, not papers. OpenAlex gives anonymous callers a small daily allowance per address. When it is used up, the run still returns the Europe PMC papers and names OpenAlex in the `sourcesFailed` column. Add your own free OpenAlex API key in `openAlexApiKey` to always include it. No key is needed to run. **Monitoring.** With `onlyNewSinceLastRun` on, the first run returns the newest papers and remembers everything it saw; every later run returns only papers it has not returned before. A paper is recognised by its DOI, its PubMed ID or its title, so a record that gains a DOI a week later is not reported twice. A run with nothing new returns one row with `paperCount` 0 and is not charged. ### Output One row per paper, for example: | query | found | status | searchQuery | paperCount | monitorStatus | truncated | sourcesChecked | sourcesFailed | papers | title | authors | firstAuthor | authorCount | journal | publishedAt | publicationType | isPreprint | preprintServer | doi | pmid | pmcid | openalexId | abstract | isOpenAccess | fullTextUrl | foundIn | paperUrl | sourceUrl | isNew | firstSeenAt | scrapedAt | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | llm | true | OK | | | | | | | \ | | <authors> | <first author> | <number of authors> | <journal or preprint server> | <published on> | <type> | <is a preprint> | <preprint server> | <doi> | <pubmed id> | <pubmed central id> | <openalex id> | <abstract> | <open access> | <free full text> | <found in> | <paper link> | <index record> | \<is this paper new?> | <first seen on a run> | 1970-01-01T00:00:00.000Z | Three real rows from a run on `llm` (2026-10-11), trimmed to the main columns: | title | journal | publishedAt | publicationType | doi | foundIn | | --- | --- | --- | --- | --- | --- | | A multi-model LLM framework for AI-assisted psychological scale development | BMC Psychology | 2026-10-11 | journal-article | 10.1186/s40359-026-05759-w | OpenAlex | | DBCLS BioHackathon 2026 report: An interactive, harmonised BioSample metadata resource | BioHackrXiv | 2026-10-10 | preprint | 10.37044/osf.io/hm9fn_v1 | Europe PMC, BioHackrXiv | | Physics-guided thermodynamic screening of H2 adsorption on alkaline-earth-modified anatase TiO2 nanoparticles | RSC advances | 2026-10-09 | journal-article | (none yet) | Europe PMC, PubMed Central | A query that matches nothing comes back as one row with `"found": false` and is never charged. A value an index does not hold is `null`, never `0` or an empty string: a brand-new PubMed Central record often has no DOI or abstract yet. Author names are returned as published; affiliations, emails and ORCID iDs are not. A preprint and its later journal version have two DOIs and are two rows. ### Pricing Pay-per-event. A flat per-run fee covers session/proxy warmup; you're billed per item only when data is actually found and returned — see `.actor/pay_per_event.json` for exact prices. A miss is never charged. ### Example runs Paste any of these into the Input tab and press Start. All three return rows with no key, no token and no account of your own beyond an Apify login. **The newest papers on one keyword.** The default shape. ```json { "queries": ["llm"], "maxItems": 20 } ``` **Two watches in one run, life-science indexes only, last 14 days.** ```json { "queries": ["CRISPR base editing", "(semaglutide OR tirzepatide) AND obesity"], "sources": "europePmc", "sinceDays": 14, "maxItems": 25 } ``` **A daily alert: only papers new since the last run, study protocols left out.** ```json { "queries": ["\"large language model\" AND radiology"], "excludeKeywords": ["study protocol"], "onlyNewSinceLastRun": true, "deltaName": "radiology-llm" } ``` ### Use it from Clay, n8n, Make, or an AI agent This actor runs synchronously over plain HTTP — call it directly from a script, a workflow tool, or an AI agent, no Apify Console needed once you have an API token. ```bash curl "https://api.apify.com/v2/acts/accountable_eel~research-literature-watch/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \ -X POST \ -H "Content-Type: application/json" \ -d '{"queries":["llm"]}' ``` **n8n.** Add an HTTP Request node: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~research-literature-watch/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body Content Type `JSON`, JSON Body `{"queries":["llm"]}` (swap in an expression from an earlier node for a real value). **Clay.** Add an "HTTP API" column: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~research-literature-watch/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body `{"queries":["{{watch query}}"]}`, mapping the row's watch query into the `queries` array. **MCP.** In Claude, Cursor, or any MCP client with the Apify MCP server, ask for "new research papers alert by keyword" — the agent will find and run this actor. # Actor input Schema ## `queries` (type: `array`): One watch per line, up to 20. Plain words are all required (CRISPR base editing); put a phrase in quotes ("large language model"); AND, OR, NOT and parentheses work. Each line is its own watch with its own memory. Accepted formats: llm, "large language model" AND radiology, CRISPR base editing, (semaglutide OR tirzepatide) AND obesity. You're only charged for the ones we actually find — a miss costs nothing. ## `maxItems` (type: `integer`): Up to 100. Caps how many papers you get (and pay for) per query in one run, newest first. With monitoring on, the cap counts new papers only, and a new paper beyond it arrives on the next run. ## `testRun` (type: `boolean`): Turn this on to test your input on a small sample before running the full list. Turn it off to process everything. ## `onlyFound` (type: `boolean`): Only keep rows where something was actually found. Misses are always free, whether or not you show them here. ## `includeKeywords` (type: `array`): Optional. Only keep results that mention at least one of these words (e.g. a job title, a city, a product name). Leave empty to keep everything. ## `excludeKeywords` (type: `array`): Optional. Drop any result that mentions one of these words. Leave empty to skip nothing. ## `maxResults` (type: `integer`): Optional. Stop the run once this many results have been found — useful for a quick, cheap sample. Leave blank for no limit. ## `sinceDays` (type: `integer`): How far back to look, by first publication date. Up to 365. For a daily alert 30 is plenty: the monitoring memory, not this window, decides what is new. ## `matchIn` (type: `string`): Title and abstract keeps the alert about papers that are on your topic. Anywhere also returns papers that only mention the words in passing. ## `sources` (type: `string`): Europe PMC carries PubMed, PubMed Central and preprints from bioRxiv, medRxiv and other servers. OpenAlex adds arXiv and every field outside the life sciences. ## `openAlexApiKey` (type: `string`): Not needed to run. Without a key OpenAlex allows a small number of anonymous searches per day per address; when that allowance is used up the run still returns the Europe PMC papers and says so in the Indexes that did not answer column. With your own free OpenAlex key, OpenAlex is always included. ## `onlyNewSinceLastRun` (type: `boolean`): On: only papers this watch has not returned before are returned and charged for. Run it on a schedule as a paper alert. Off: every matching paper is returned every time. ## `deltaName` (type: `string`): Optional. Name this watch's monitoring memory so you can tell two schedules of this actor apart. Leave empty to use one memory per query line. ## `columns` (type: `array`): Choose which pieces of information to include in each result row. All are included by default. ## `expandRows` (type: `boolean`): When on, each paper found gets its own row instead of being grouped under its watch query. You're still only charged once per watch query, no matter how many rows it produces. ## `maxConcurrency` (type: `integer`): Parallel requests. Keep conservative — this target has no browser fallback, so getting blocked costs more than slow-and-steady. ## `proxyConfiguration` (type: `object`): Apify Proxy config. This target is a free public API that needs no proxy — defaults to off, but you can turn one on if you prefer. ## Actor input object example ```json { "queries": [ "llm" ], "maxItems": 25, "testRun": false, "onlyFound": false, "includeKeywords": [], "excludeKeywords": [], "sinceDays": 30, "matchIn": "titleAbstract", "sources": "all", "onlyNewSinceLastRun": false, "deltaName": "", "columns": [ "searchQuery", "paperCount", "monitorStatus", "truncated", "sourcesChecked", "sourcesFailed", "papers", "title", "authors", "firstAuthor", "authorCount", "journal", "publishedAt", "publicationType", "isPreprint", "preprintServer", "doi", "pmid", "pmcid", "openalexId", "abstract", "isOpenAccess", "fullTextUrl", "foundIn", "paperUrl", "sourceUrl", "isNew", "firstSeenAt" ], "expandRows": true, "maxConcurrency": 1, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (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 '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = { "queries": [ "llm" ], "includeKeywords": [], "excludeKeywords": [] }; // Run the Actor and wait for it to finish const run = await client.actor("accountable_eel/research-literature-watch").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": ["llm"], "includeKeywords": [], "excludeKeywords": [], } # Run the Actor and wait for it to finish run = client.actor("accountable_eel/research-literature-watch").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": [ "llm" ], "includeKeywords": [], "excludeKeywords": [] }' | apify call accountable_eel/research-literature-watch --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,accountable_eel/research-literature-watch" } } } ``` 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/vGYPU71pj2Dm1S23D/builds/ej3QiBFWP3gY7bUST/openapi.json