PubMed Watchlist Monitor - Europe PMC API

Re-check the PubMed IDs on your literature or pharmacovigilance list. Get title, status, citation and open-access changes — and skip the papers that did not move.

This Actor takes a caller-owned list of PMIDs, reads Europe PMC, and writes one structured metadata row per ID. Pass the previous run's snapshot back in and you get INITIAL, UNCHANGED or CHANGED. Abstracts are not billed as full text. This is not a PubMed search dump.

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What this Actor does

You already have PMIDs from a review, a trial bibliography, or a competitor paper list. You want a scheduled check for revision dates, citation counts, publication status and open-access flags — without paying a large start fee for a handful of IDs.

That is the job: a PMID watchlist, not a literature crawl.

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What you get

{
  "schemaVersion": 1,
  "id": "38720000",
  "status": "ok",
  "pmid": "38720000",
  "doi": "10.1038/s41586-024-00000-0",
  "title": "Example article title from Europe PMC",
  "authorString": "Example Author",
  "journalTitle": "Nature",
  "pubYear": "2024",
  "publicationStatus": "epublish",
  "isOpenAccess": "Y",
  "citedByCount": 12,
  "dateOfRevision": "2024-05-10",
  "firstPublicationDate": "2024-05-09",
  "changeType": "INITIAL",
  "changedFields": [],
  "checkedAt": "2026-09-06T12:00:00.000Z",
  "sourceUrl": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:38720000%20AND%20SRC:MED&format=json&resultType=core",
  "error": null
}

PMID 38720000 is a public example identifier, not a customer or endorsement. Field values above are illustrative of shape. Missing source strings are null.

---

Main use cases

• Literature watchlists. Re-check a fixed PMID set after each Europe PMC update.
• Citation and OA movement. See when citedByCount or isOpenAccess changes.
• Revision tracking. dateOfRevision is a compared field — useful for living reviews.
• Clinops + publications. Pair PMIDs with NCT IDs in a separate Actor (below).
• n8n / MCP / backend jobs. Start the run from a server that holds APIFY_TOKEN.

---

Quick start

{
  "pmids": ["38720000"],
  "maxItems": 1
}

Run it, open the dataset, and save NEXT_SNAPSHOT from the default key-value store.

---

Repeat workflow

1. Keep one PMID watchlist per customer, trial, or review (1–50 IDs).
2. Start a bounded run. Schedule it yourself if you need a cadence.
3. Save NEXT_SNAPSHOT in your private workflow state.
4. On the next run pass it as previousSnapshot and set onlyChanges: true.
5. Route changeType: CHANGED rows for review. Inspect error rows and SUMMARY separately.

---

Input

Field	Type	Default	What it does
pmids	array	—	1–50 numeric PubMed identifiers as strings. Duplicates checked once.
maxItems	integer	50	1–50. Must cover all unique IDs.
onlyChanges	boolean	false	Suppress unchanged successful records without charging them.
previousSnapshot	object	—	Prior NEXT_SNAPSHOT with kind: "pubmed".

---

Pricing

Event	Price	When it happens
Successful watchlist result	$0.0025	One successful PMID check written to the dataset
Actor start	none	No custom start fee

You are not charged for: failed requests, parse failures, retries, duplicate IDs, invalid input, or unchanged records suppressed by onlyChanges.

Worked example. 40 PMIDs weekly, 3 changed after the first run → about $0.0075 that week in Actor event charges.

How this compares

Actor	Price per result	Per-run start	Job
This Actor	$0.0025	none	Caller-owned PMID watchlist
easyapi/pubmed-scraper (Store card, 2026-09-06)	$0.00299	$0.09	Search / dump oriented

A 20-ID refresh costs $0.05 here and about $0.15 on a $0.00299 + $0.09 start card. Competitor prices change — check the live Store cards.

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Using the API

curl --fail -X POST "https://api.apify.com/v2/acts/technicaldost~pubmed-europepmc-watchlist-monitor/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"pmids":["38720000"],"maxItems":1}'

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('technicaldost/pubmed-europepmc-watchlist-monitor').call({
    pmids: ['38720000'],
    maxItems: 1,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("technicaldost/pubmed-europepmc-watchlist-monitor").call(run_input={
    "pmids": ["38720000"],
    "maxItems": 1,
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["pmid"], row["publicationStatus"], row["changeType"])

n8n. HTTP Request to /v2/acts/technicaldost~pubmed-europepmc-watchlist-monitor/runs with Authorization: Bearer from credentials. Poll, then read the dataset and NEXT_SNAPSHOT.

MCP / agents. Server-side tool only. Never expose the token to a public client.

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Limitations

• Metadata only. Abstracts, PDFs and publisher HTML are out of scope.
• This is not a clinical conclusion, evidence grade, or systematic-review product.
• Europe PMC availability governs results. One request at a time, no automatic retries.
• At most 1,000 snapshot records are retained.

Source: public Europe PMC web service. Not affiliated with NCBI, NIH, EMBL-EBI or Europe PMC.

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Related Actors

• ClinicalTrials.gov NCT Status Monitor — status and enrollment on NCT IDs you already track.
• SEC EDGAR Filing Monitor — new-only public-company filings.

---

Changelog

See CHANGELOG.md. Release 1.0.0 (2026-09-06): caller-owned PMID watchlists, citation/OA/revision deltas, $0.0025 per successful result, no start fee.

Output example

Each result is one dataset item. A real item from a test run (long fields shortened):

{
  "schemaVersion": 1,
  "id": "38720000",
  "status": "ok",
  "pmid": "38720000",
  "doi": "10.1038/s41591-024-02982-z",
  "title": "BiTE therapy for rheumatoid arthritis.",
  "authorString": "Humby F, Kirkham B, Taams L.",
  "journalTitle": "Nature medicine",
  "pubYear": "2024",
  "publicationStatus": "ppublish",
  "isOpenAccess": "N",
  "citedByCount": 2
}

Use PubMed Watchlist Monitor with AI agents (MCP)

Give Claude, ChatGPT, Cursor, VS Code or any MCP client this Actor as a tool through the hosted Apify MCP server. The agent sees the input fields with descriptions and example values, runs the Actor, and reads the results.

MCP server URL (this Actor only):

https://mcp.apify.com/?tools=technicaldost/pubmed-europepmc-watchlist-monitor

Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/pubmed-europepmc-watchlist-monitor" --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Cursor, VS Code, Claude Desktop and other clients (mcp.json or the client's MCP settings):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/pubmed-europepmc-watchlist-monitor",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Clients that support sign-in (such as Claude.ai connectors) can use the URL without a token and log in to Apify instead. Get your token in Apify Console → Settings → API & Integrations, or generate a ready config for your client at mcp.apify.com. In the agent the tool is named technicaldost--pubmed-europepmc-watchlist-monitor; ask it, for example, to "run PubMed Watchlist Monitor with {"pmids": ["38720000"]}".

AI agents without an Apify account can also run and pay for this Actor per request with x402 agentic payments.

Run PubMed Watchlist Monitor via API

Run the Actor and get its results in one call (replace YOUR_APIFY_TOKEN):

curl -X POST "https://api.apify.com/v2/acts/technicaldost~pubmed-europepmc-watchlist-monitor/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"pmids": ["38720000"]}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/pubmed-europepmc-watchlist-monitor").call(run_input={"pmids": ["38720000"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/pubmed-europepmc-watchlist-monitor').call({"pmids": ["38720000"]});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Long runs: start them with POST /v2/acts/technicaldost~pubmed-europepmc-watchlist-monitor/runs and fetch the dataset when the run finishes, or receive a webhook.

FAQ

Can I use PubMed Watchlist Monitor with AI agents like Claude or ChatGPT?

Yes. Connect the Apify MCP server with ?tools=technicaldost/pubmed-europepmc-watchlist-monitor (see above) and the agent can run the Actor and read its results on its own.

Can I call PubMed Watchlist Monitor from my own code?

Yes. Use the REST API, or the official Python and JavaScript clients shown above. Results are available as JSON, CSV, Excel, XML or HTML.

How do I run it on a schedule?

Save your input as a task in Apify Console and add a schedule (for example, daily). Use webhooks or integrations to send each run's results onward.

Is it legal to use this Actor?

It works with publicly available data. Make sure your use complies with the source website's terms and with data protection laws such as GDPR, especially for personal data.

Something doesn't work or I need a feature. What should I do?

Open an issue in the Issues tab on this Actor's page with an example input, and we'll look into it.