Met Museum Scraper - Artworks, Artists & Images

Scrape the Metropolitan Museum of Art collection in bulk. Extract object title, artist, nationality, dates, medium, dimensions, department, classification, culture, credit line, public-domain status and image URLs to CSV/JSON. No API key, no login.

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What does the Met Museum Scraper do?

This Actor turns Met Museum data into a structured dataset. You point it at one department or a search across the collection, it walks the result pages one after another, and it writes one clean row per object into your dataset — ready to export as JSON, CSV or Excel, or to pull straight from the Apify API.

The Metropolitan Museum of Art publishes its entire 500,000-object catalogue through a keyless API, with much of it released into the public domain. The index endpoint returns object IDs only, so the Actor resolves each record in a bounded parallel pool — that is what turns a list of numbers into rows carrying artist, medium, provenance and image links. Pagination is followed automatically until it runs out of results, hits your page limit or hits your Max items cap, whichever comes first. Every row is de-duplicated across the whole run, so you are never billed twice for the same object.

There is no API key, no login and no browser involved. That keeps runs fast and cheap, and it means you can schedule the Actor without worrying about credentials expiring.

Who is it for?

• AI and ML teams sourcing public-domain imagery with provenance.
• Publishers and documentary researchers finding reproducible artwork.
• Art historians analysing a collection quantitatively.
• Educators assembling primary-source image sets.
• Developers building discovery tools over open museum data.

Use cases

• Export a department's holdings with artist and date for every object.
• Filter to public-domain works you can legally reproduce.
• Analyse how a collection is distributed by culture, period or medium.
• Build a labelled art image dataset with full attribution.
• Find which objects are currently on view in the galleries.

Why use this Met Museum Scraper?

• 🔑 Keyless — no account, no API token, no cookies to paste.
• 📦 34 fields per object — everything the source exposes, already typed.
• 📄 Real pagination — it walks page after page instead of returning the first screen.
• 🎯 Precise caps — Max items stops the run exactly where you want it, so the bill is predictable.
• 📊 Export anywhere — JSON, CSV, Excel or HTML, plus the Apify API and integrations.
• 💸 Pay per result — you pay for rows you actually receive, with no platform fees to calculate.

What data can you extract?

Every run produces one row per object, with these fields:

Field	Type	Description
objectId	string	Met object identifier
title	string	Object title
objectUrl	string	Met collection page for the object
artistDisplayName	string	Artist as displayed by the museum
artistNationality	string	Artist nationality when recorded
artistBeginDate	string	Artist's birth year as recorded
artistEndDate	string	Artist's death year as recorded
objectDate	string	Date as displayed, often a range or circa
objectBeginDate	number	Earliest year the museum assigns
objectEndDate	number	Latest year the museum assigns
medium	string	Materials and technique
dimensions	string	Dimensions as recorded
department	string	Curatorial department
classification	string	Object classification, e.g. Paintings or Ceramics
culture	string	Culture of origin when recorded
period	string	Period when recorded
dynasty	string	Dynasty when recorded
country	string	Country of origin when recorded
creditLine	string	Acquisition credit line
accessionNumber	string	Museum accession number
accessionYear	string	Year the object entered the collection
isHighlight	boolean	Whether the museum marks it as a highlight
isPublicDomain	boolean	Whether the image is released into the public domain
isOnView	boolean	Whether a gallery number is assigned
galleryNumber	string	Gallery the object is displayed in
primaryImage	string	Full-resolution image URL
primaryImageSmall	string	Web-resolution image URL
additionalImageCount	number	Number of additional images
tags	string	Subject tags, separated by a pipe
objectWikidataUrl	string	Wikidata link for the object when recorded
artistWikidataUrl	string	Wikidata link for the artist when recorded
query	string	Search term or department this row came from
page	number	Batch the object was resolved in
scrapedAt	string	ISO timestamp of extraction

Output example

{
  "objectId": "435948",
  "title": "Portrait of a Bearded Man in Black",
  "objectUrl": "https://www.metmuseum.org/art/collection/search/435948",
  "artistDisplayName": "Corneille de Lyon",
  "artistNationality": "Netherlandish",
  "artistBeginDate": "1533",
  "artistEndDate": "1575",
  "objectDate": null,
  "objectBeginDate": 1533,
  "objectEndDate": 1575,
  "medium": "Oil on wood",
  "dimensions": "6 3/4 x 6 1/4 in. (17.1 x 15.9 cm)",
  "department": "European Paintings",
  "classification": "Paintings",
  "culture": null,
  "period": null,
  "dynasty": null,
  "country": null,
  "creditLine": "Bequest of George D. Pratt, 1935",
  "accessionNumber": "1978.301.6",
  "accessionYear": "1978",
  "isHighlight": false,
  "isPublicDomain": true,
  "isOnView": false,
  "galleryNumber": null,
  "primaryImage": "https://images.metmuseum.org/CRDImages/ep/original/DP-13587-001.jpg",
  "primaryImageSmall": "https://images.metmuseum.org/CRDImages/ep/web-large/DP-13587-001.jpg",
  "additionalImageCount": 0,
  "tags": "Men | Portraits",
  "objectWikidataUrl": "https://www.wikidata.org/wiki/Q19913191",
  "artistWikidataUrl": "https://www.wikidata.org/wiki/Q720941",
  "query": "department 11",
  "page": 1,
  "scrapedAt": "2026-09-21T10:18:44.902Z"
}

How to use

Option A — one department

{
  "departmentId": 11,
  "imagesOnly": true,
  "maxItems": 300,
  "searchQuery": ""
}

1. Open the Actor and fill in the first field.
2. Set the page limit and Max items to bound the run.
3. Click Start, then export from the Output tab.

Option B — a search across the collection

{
  "departmentId": 0,
  "imagesOnly": true,
  "maxItems": 500,
  "searchQuery": "monet"
}

Everything in the first field is processed independently, so you can batch several targets into one run and split them apart afterwards.

Input parameters

Parameter	Type	Default	Description
searchQuery	string	–	Search the collection, e.
departmentId	integer	0	Restrict to one curatorial department, e.
imagesOnly	boolean	true	Only include objects that have a photograph.
maxItems	integer	300	Stop after this many objects.
maxConcurrency	integer	2	Parallel requests.
proxyConfiguration	object	{"useApifyProxy": true}	Proxy used to fetch pages.

Tips for best results

• Leave the search term empty to walk the catalogue in object-ID order — about 500,000 records.
• Department narrows the walk to one curatorial area; there are nineteen of them.
• Images only restricts a search to objects that actually have a photograph.
• isPublicDomain true is the filter to use when you intend to republish an image.
• primaryImage is full resolution and can be tens of megabytes; primaryImageSmall is the web copy.
• The index endpoint returns IDs only, so each object costs one request — roughly a sixth of a second.
• objectBeginDate and objectEndDate are numeric and sortable; objectDate is the human label.
• Many records are catalogue entries without photographs, so image fields are legitimately empty there.
• Always keep objectUrl and creditLine with any image you republish, for attribution.
• Pair with the Art Institute and Cleveland Museum scrapers for a wider open-collection set.

Run outcomes: an empty result is not the same as a blocked run

A crawl that was refused and a query that genuinely has no matches both produce an empty dataset. Treating them as the same thing makes the output unusable for monitoring, so every run is classified and an unverified emptiness is never reported as success.

Outcome	Run status	Meaning
COMPLETED	Succeeded	Everything requested was fetched and rows were saved.
PARTIAL	Succeeded	Rows were saved, but some pages were unreachable.
EMPTY_RESULT	Succeeded	Pages were fetched and parsed and this query really has no objects.
BLOCKED	Failed	Every request was refused with HTTP 403/429/503.
NOT_FOUND	Failed	The source answered 404; check the address or filters.
FETCH_FAILED	Failed	Nothing could be fetched for transport reasons.
INCOMPLETE_NO_ROWS	Failed	Pages were skipped and nothing was saved, so an empty result cannot be trusted.

The rule behind the table: a run that fetched nothing can never finish as Succeeded. Each run also writes a SUMMARY record to the key-value store with pages requested, pages fetched, pages skipped, HTTP request and retry counts, a per-status breakdown, transport errors and the termination reason — so the row count is always reconcilable with what the run actually did.

Integrations

Send results straight into the tools you already use: Google Sheets, Slack, Zapier, Make, Airtable or any Webhook. You can also schedule the Actor to run hourly, daily or weekly and have each run append to the same dataset, which is how you build a price or availability history rather than a one-off snapshot.

API usage

Run the Actor and collect results from any language. Replace <YOUR_TOKEN> with your Apify API token.

cURL

curl -X POST "https://api.apify.com/v2/acts/logiover~met-museum-collection-scraper/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"departmentId": 11, "imagesOnly": true, "maxItems": 300, "searchQuery": ""}'

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_TOKEN>' });
const run = await client.actor('logiover/met-museum-collection-scraper').call({"departmentId": 11, "imagesOnly": true, "maxItems": 300, "searchQuery": ""});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient('<YOUR_TOKEN>')
run = client.actor('logiover/met-museum-collection-scraper').call(run_input={"departmentId": 11, "imagesOnly": true, "maxItems": 300, "searchQuery": ""})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Use with AI agents (MCP)

This Actor is available through the Apify MCP server, so an AI agent can call it as a tool. Point your agent at https://mcp.apify.com and it can run the Met Museum Scraper on demand — for example: "Pull the first 500 objects from Met Museum and summarise what you find." The agent receives the same structured rows you would get from the UI.

FAQ

Do I need a Met Museum account or API key?

No. The Actor reads publicly available data only. There is nothing to authenticate and no credentials to rotate.

How many objects can I get in one run?

As many as the source exposes. Raise the page limit and Max items together; the run stops at whichever limit it reaches first.

Why did I get fewer rows than I asked for?

The source ran out of objects. That is normal for narrow searches — broaden the query or add more targets to one run.

Are results de-duplicated?

Yes. Each object is emitted once per run, even when it appears on several pages, so you are never billed twice for the same record.

Why are some fields empty?

Met Museum does not publish every attribute for every object. Empty means the source did not supply it, not that extraction failed.

What export formats are supported?

JSON, CSV, Excel, HTML and RSS from the Output tab, plus the Apify API and any integration you connect.

How fast is it?

It is pure HTTP with no browser, so a page of results typically takes a second or two. Raise Max concurrency carefully — the source rate-limits aggressive crawling.

Can I schedule it?

Yes. Use the Apify scheduler to run it on any interval and append each run to the same dataset for time-series analysis.

Does it work behind a proxy?

It uses Apify Proxy automatically. You can switch groups or supply your own proxies in Proxy configuration.

How often does the data change?

Met Museum updates continuously. Re-run whenever you need current data; the Actor always reads the live source, never a cache.

Is the output schema stable?

Yes. Field names and types are fixed, so downstream pipelines will not break between runs.

What if the source changes its format?

Open an issue on the Issues tab and it gets fixed. The Actor is actively maintained.

Is it legal?

This Actor reads only publicly available data from Met Museum — the same content any visitor or client sees without logging in. It does not bypass authentication, does not collect private data and does not attempt to defeat access controls. You are responsible for how you use the output: respect the source's terms of service, applicable copyright, and data-protection law such as GDPR where personal data is involved. Scraping public data is generally lawful in the EU and the US, but the responsibility for the downstream use of that data sits with you.

Related scrapers

• Art Institute Scraper — Open-access artworks
• Cleveland Museum Scraper — CC0 collection
• Library of Congress Scraper — Historical imagery
• Openverse Scraper — Openly licensed media