Wikidata Entity Scraper — Labels, Claims & Sitelinks | from $0.50/1K

Built for knowledge-graph builders, entity-resolution pipelines, and AI agents that need structured Wikidata records by Q-ID or keyword. Official APIs only — no proxy, no auth, zero COGS.

Extract structured data from Wikidata entities via the official public APIs. No proxy, no authentication required.

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What you get

For each entity (fetched by Q-ID or discovered via search):

Field	Description
entity_id	Wikidata Q-ID (e.g. Q42)
label	Human-readable name in requested language
description	Short description (e.g. "British science fiction writer")
aliases	Known alternative names
instance_of	What type of entity this is (Q-IDs from P31)
key_claims	Selected property values (dates, genders, occupations, nationalities…)
sitelinks_count	Number of Wikipedia editions this entity has an article on
url	Canonical Wikidata entity URL
parse_confidence	0.0–1.0 quality score; 1.0 = all expected fields present
warnings	List of field-level quality warnings

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Inputs

Basic

Parameter	Type	Description	Default
entityIds	array	Wikidata Q-IDs to fetch directly	["Q42", "Q937"]
searchQueries	array	Full-text search queries	[]
language	string	Language code for labels/descriptions	"en"
maxItems	integer	Max total entities to return (0 = unlimited)	50
maxSearchResults	integer	Max results per search query (1–50)	10

Advanced

Parameter	Type	Description	Default
claimProperties	array	P-value property IDs to extract	["P31","P21","P27","P569","P570","P19","P106"]
maxClaimsPerProperty	integer	Max values per property (0 = all)	5

Default properties extracted:

• P31 — instance of (what kind of thing this is)
• P21 — sex or gender
• P27 — country of citizenship
• P569 — date of birth
• P570 — date of death
• P19 — place of birth
• P106 — occupation

Other useful properties: P18 (image), P856 (website), P17 (country), P131 (located in), P625 (coordinates).

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Example

Input:

{
  "entityIds": ["Q42", "Q7186"],
  "language": "en",
  "claimProperties": ["P31", "P569", "P570", "P106"]
}

Output record for Q42:

{
  "entity_id": "Q42",
  "label": "Douglas Adams",
  "description": "British science fiction writer and humorist (1952–2001)",
  "aliases": ["Douglas Noel Adams"],
  "instance_of": ["Q5"],
  "key_claims": {
    "P31": ["Q5"],
    "P569": ["1952-03-11T00:00:00Z"],
    "P570": ["2001-05-11T00:00:00Z"],
    "P106": ["Q214917", "Q28389", "Q6625963"]
  },
  "sitelinks_count": 132,
  "url": "https://www.wikidata.org/wiki/Q42",
  "language": "en",
  "query": "Q42",
  "source": "entity_id",
  "scraped_at": "2026-05-31T10:00:00Z",
  "parse_confidence": 1.0,
  "warnings": []
}

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Notes on claim values

Claim values are decoded to human-readable strings:

• wikibase-item → Q-ID string ("Q5", "Q6581097")
• time → ISO date string ("1952-03-11T00:00:00Z")
• string / external-id → raw string
• quantity → "42 Q11573" (amount + unit Q-ID)

To look up what a Q-ID means (e.g. "Q5" = human, "Q145" = United Kingdom), search it on wikidata.org.

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Pricing

Pay per entity: from $0.50 / 1,000 entities (PPE). Apify automatically charges the run owner. No monthly subscription. The first few seconds of each run are covered by Apify.

Volume	Cost
100 entities	~$0.05
1,000 entities	~$0.50
10,000 entities	~$5.00

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FAQ

Do I need a proxy or API key? No. Wikidata is a fully public API — no credentials, no proxy required.

What output formats are available? JSON (default), CSV, and Excel — downloadable from the Apify dataset UI or via the REST API.

Can I schedule this to run automatically? Yes. Apify's scheduler runs this on any cron schedule and can push results via webhook to your pipeline automatically.

What if a Q-ID doesn't exist or returns empty? The actor logs a warning and skips the entity — no crash. Missing Q-IDs appear in the OUTPUT.failedDetails summary at the end of the run.

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Why this actor

• Official APIs only — EntityData REST + Action API. No DOM scraping, no parsing fragility.
• Zero cost — Wikidata is public, no proxy or authentication needed.
• Configurable properties — extract exactly the P-values you need.
• parse_confidence field — machine-detectable data quality in every row.
• Multi-language — labels and descriptions in any Wikidata language.

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Not affiliated with Wikimedia Foundation. Uses the official Wikidata public APIs.

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Use with AI agents (MCP)

This actor is available as an MCP tool for Claude, GPT-4, and other AI agents that support the Model Context Protocol:

https://mcp.apify.com/?tools=bovi/wikidata-scraper

Feed any Q-ID or search term and get back structured entity data — ideal for knowledge-graph enrichment, entity disambiguation, and AI research pipelines.

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vs. competitors

	This actor	Typical Wikidata scraper
Data source	Official Wikidata REST + Action APIs	HTML / DOM scraping
P-values (claims)	Configurable selection	Rarely exposed
parse_confidence	✓	No
Proxy needed	No	Often required
Price	from $0.50/1K	$2–5/1K

Integrations

Built for knowledge-graph builders and entity-resolution pipelines consuming structured Wikidata records by Q-ID or keyword — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.