# Met Museum Open Access Art Scraper (`jungle_synthesizer/met-museum-open-access-art-scraper`) Actor Scrape The Met's open-access collection API. Returns full metadata for 490k+ objects: title, artist, department, medium, dimensions, classification, culture, credit line, AAT tags, and CC0 image URLs. Modes: keyword search, department walk, incremental, and direct object-ID lookup. - **URL**: https://apify.com/jungle\_synthesizer/met-museum-open-access-art-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Met Museum Open Access Art Scraper Scrape artwork records from The Metropolitan Museum of Art's open-access collection API. Returns full metadata for 490k+ objects including title, artist, department, medium, dimensions, classification, culture, period, credit line, AAT subject tags, and CC0 image URLs. ### What you get Each scraped record contains: | Field | Description | |-------|-------------| | `object_id` | Numeric Met Museum object ID | | `accession_number` | Museum accession number | | `accession_year` | Year the object was accessioned | | `is_public_domain` | CC0 licence flag | | `is_highlight` | Met highlight designation | | `is_on_view` | Currently on display | | `title` | Object title | | `artist_display_name` | Artist name | | `artist_display_bio` | Artist biographical note | | `artist_nationality` | Artist nationality | | `artist_begin_date` | Artist birth year | | `artist_end_date` | Artist death year | | `artist_wikidata_url` | Artist Wikidata URL | | `artist_ulan_url` | Artist Getty ULAN URL | | `object_date` | Creation date (human-readable) | | `object_begin_date` | Earliest creation year (integer) | | `object_end_date` | Latest creation year (integer) | | `medium` | Materials (e.g. "Oil on canvas") | | `dimensions` | Physical dimensions | | `classification` | Object type (e.g. "Paintings", "Prints") | | `department` | Museum department | | `culture` | Culture of origin | | `period` | Historical period | | `dynasty` | Dynasty (for antiquities) | | `credit_line` | Acquisition credit line | | `gallery_number` | Gallery number | | `object_name` | Object type (e.g. "Painting", "Vase") | | `primary_image_url` | Full-resolution CC0 image URL | | `primary_image_small_url` | Web-size CC0 image URL | | `additional_image_urls` | Pipe-separated additional image URLs | | `tags` | Pipe-separated AAT subject tags | | `object_url` | Met collection page URL | | `object_wikidata_url` | Object Wikidata URL | | `metadata_date` | Record last updated date | | `repository` | Repository name | ### Modes #### Search mode (default) Discover objects by keyword query with optional filters: ```json { "mode": "search", "query": "van gogh", "hasImages": true, "departmentId": 11, "dateBegin": 1880, "dateEnd": 1920, "maxItems": 100 } ```` Filters available in search mode: `departmentId`, `hasImages`, `isHighlight`, `isOnView`, `dateBegin`, `dateEnd`, `geoLocation`, `medium`. #### Walk mode Iterate the full collection or a department without a keyword: ```json { "mode": "walk", "departmentId": 11, "maxItems": 500 } ``` Omit `departmentId` to walk the entire 490k+ object collection. #### Incremental mode Fetch only objects whose metadata was updated on or after a date: ```json { "mode": "incremental", "metadataDate": "2026-01-01", "maxItems": 1000 } ``` Use this for scheduled runs that pick up newly added or corrected records. #### By-ID mode Fetch specific objects by their Met object ID: ```json { "mode": "by_ids", "objectIds": ["436535", "436529", "436944"], "maxItems": 50 } ``` ### Department IDs | ID | Department | |----|-----------| | 1 | American Wing | | 3 | Ancient West Asian Art | | 4 | Arms and Armor | | 5 | Arts of Africa, Oceania, and the Americas | | 6 | Asian Art | | 7 | The Cloisters | | 8 | The Costume Institute | | 9 | Drawings and Prints | | 10 | Egyptian Art | | 11 | European Paintings | | 12 | European Sculpture and Decorative Arts | | 13 | Greek and Roman Art | | 14 | Islamic Art | | 15 | The Robert Lehman Collection | | 16 | The Libraries | | 17 | Medieval Art | | 18 | Musical Instruments | | 19 | Photographs | | 21 | Modern Art | ### Notes on image URLs Image URLs point to the Met's CDN (`images.metmuseum.org`) and are served under the CC0 licence for public-domain objects. This actor exports URL strings only — it does not download or rehost pixel data. ### Data source Data is sourced from the Metropolitan Museum of Art's public collection API at `collectionapi.metmuseum.org`. No authentication is required. The Met requests polite use — this actor operates well below the advised 80 req/sec cap. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `mode` (type: `string`): How to discover objects: "search" (keyword + filters), "walk" (full collection or department), "incremental" (changed since a date), or "by\_ids" (explicit object ID list). ## `query` (type: `string`): Keyword query string (required when mode=search). Examples: "van gogh", "impressionism", "japanese woodblock". ## `departmentId` (type: `integer`): Filter by department. Paintings=11, Drawings & Prints=9, European Sculpture=12, Modern Art=21, Greek & Roman=13, Egyptian Art=10, Asian Art=6, American Wing=1. Leave blank for all. ## `hasImages` (type: `boolean`): When true, only return objects that have a primary image (applies to search and walk modes). ## `isHighlight` (type: `boolean`): When true, only return objects designated as Met highlights (applies to search and walk modes). ## `isOnView` (type: `boolean`): When true, only return objects currently on view at the museum. ## `dateBegin` (type: `integer`): Earliest object creation year (search mode only). Example: 1800. ## `dateEnd` (type: `integer`): Latest object creation year (search mode only). Example: 1900. ## `geoLocation` (type: `string`): Filter by geographic location (search mode only). Example: "France", "Japan", "Egypt". ## `medium` (type: `string`): Filter by medium (search mode only). Example: "oil on canvas", "watercolor", "woodblock". ## `metadataDate` (type: `string`): Return only objects updated on or after this date (mode=incremental). Format: YYYY-MM-DD. Example: 2026-01-01. ## `objectIds` (type: `array`): Explicit list of Met object IDs to fetch (mode=by\_ids). Example: \["436535", "436529"]. ## `maxItems` (type: `integer`): Maximum number of artwork records to return. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "search", "query": "van gogh", "hasImages": false, "isHighlight": false, "isOnView": false, "objectIds": [ "436535", "436529" ], "maxItems": 10 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "search", "query": "van gogh", "objectIds": [ "436535", "436529" ], "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/met-museum-open-access-art-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "search", "query": "van gogh", "objectIds": [ "436535", "436529", ], "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/met-museum-open-access-art-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "search", "query": "van gogh", "objectIds": [ "436535", "436529" ], "maxItems": 10 }' | apify call jungle_synthesizer/met-museum-open-access-art-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/met-museum-open-access-art-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Met Museum Open Access Art Scraper", "description": "Scrape The Met's open-access collection API. Returns full metadata for 490k+ objects: title, artist, department, medium, dimensions, classification, culture, credit line, AAT tags, and CC0 image URLs. Modes: keyword search, department walk, incremental, and direct object-ID lookup.", "version": "0.1", "x-build-id": "Kh91dU30YaK08L44J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~met-museum-open-access-art-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-met-museum-open-access-art-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/jungle_synthesizer~met-museum-open-access-art-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-met-museum-open-access-art-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/jungle_synthesizer~met-museum-open-access-art-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-met-museum-open-access-art-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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "mode": { "title": "Mode", "enum": [ "search", "walk", "incremental", "by_ids" ], "type": "string", "description": "How to discover objects: \"search\" (keyword + filters), \"walk\" (full collection or department), \"incremental\" (changed since a date), or \"by_ids\" (explicit object ID list).", "default": "search" }, "query": { "title": "Search Query", "type": "string", "description": "Keyword query string (required when mode=search). Examples: \"van gogh\", \"impressionism\", \"japanese woodblock\"." }, "departmentId": { "title": "Department ID", "type": "integer", "description": "Filter by department. Paintings=11, Drawings & Prints=9, European Sculpture=12, Modern Art=21, Greek & Roman=13, Egyptian Art=10, Asian Art=6, American Wing=1. Leave blank for all." }, "hasImages": { "title": "Has Images Only", "type": "boolean", "description": "When true, only return objects that have a primary image (applies to search and walk modes).", "default": false }, "isHighlight": { "title": "Highlights Only", "type": "boolean", "description": "When true, only return objects designated as Met highlights (applies to search and walk modes).", "default": false }, "isOnView": { "title": "On View Only", "type": "boolean", "description": "When true, only return objects currently on view at the museum.", "default": false }, "dateBegin": { "title": "Date Begin", "type": "integer", "description": "Earliest object creation year (search mode only). Example: 1800." }, "dateEnd": { "title": "Date End", "type": "integer", "description": "Latest object creation year (search mode only). Example: 1900." }, "geoLocation": { "title": "Geographic Location", "type": "string", "description": "Filter by geographic location (search mode only). Example: \"France\", \"Japan\", \"Egypt\"." }, "medium": { "title": "Medium", "type": "string", "description": "Filter by medium (search mode only). Example: \"oil on canvas\", \"watercolor\", \"woodblock\"." }, "metadataDate": { "title": "Metadata Date (Incremental)", "type": "string", "description": "Return only objects updated on or after this date (mode=incremental). Format: YYYY-MM-DD. Example: 2026-01-01." }, "objectIds": { "title": "Object IDs (By-ID mode)", "type": "array", "description": "Explicit list of Met object IDs to fetch (mode=by_ids). Example: [\"436535\", \"436529\"].", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of artwork records to return.", "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 } } } } } } } } } } ```