# Wikidata Scraper - Knowledge Graph Entity Data (`scrapesage/wikidata-scraper`) Actor

Search Wikidata or resolve Q-ids to clean structured entity data: label, description, aliases, instance-of, country, industry, founders, CEO, headquarters, website, coordinates, ISIN and the Wikipedia link. Entity resolution for AI agents and data enrichment. No API key, no browser.

- **URL**: https://apify.com/scrapesage/wikidata-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** Agents, Integrations, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.55 / 1,000 entity scrapeds

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Wikidata Scraper - Knowledge Graph Entity Data

Search **Wikidata** - the free knowledge graph behind Wikipedia - or resolve **Q-ids** directly, and get
clean structured rows for every entity: **label**, **description**, **aliases**, **instance-of**,
**country**, **industry**, **founders**, **CEO**, **headquarters**, **official website**,
**coordinates**, **ISIN**, **revenue** and the **Wikipedia link**. Built for **entity resolution** and
data enrichment. No key, no browser.

### What you get per entity

| Field | Meaning |
|---|---|
| `id` / `label` / `description` / `aliases` | Q-id, name, one-line description and alternate names |
| `instanceOf` / `subclassOf` / `dataType` | What kind of thing it is |
| `country` / `headquartersLocation` / `coordinates` | Location data |
| `industry` / `employees` / `founders` / `ceo` / `revenue` | Company facts where present |
| `officialWebsite` / `officialName` / `legalForm` / `isin` / `stockExchange` | Corporate identifiers |
| `ownedBy` / `parentOrg` / `partOf` / `inception` | Ownership and history |
| `claimPropertyCount` / `wikipediaUrl` / `wikidataUrl` | Richness signal and canonical links |

### Input

```json
{ "searchQueries": ["Tesla", "Marie Curie"], "language": "en", "maxItemsPerQuery": 10 }
```

- **Search terms** - names or terms, one per line; each resolves to matching entities.
- **Q-ids** - exact entity lookups (e.g. `Q42`). **Language** - label/description language (falls back to English).
- **Import from a file** - paste a list, or link a public `.txt`/`.csv`, a Google Sheet/Drive link, or an
  Apify key-value-store record (terms and Q-ids auto-detected). **Output fields** trim every record.

Leave everything empty and the run returns a small free sample so you can see the shape first.

### Reliability

Reads the official [Wikidata API](https://www.wikidata.org/w/api.php) (`wbsearchentities` +
`wbgetentities`) - public, keyless, no anti-bot, batched 50 entities per request. A search that returns
nothing bills **$0**.

### Honest limits

- **Claims are a curated high-value subset** (instance-of, country, industry, founders, CEO, website,
  coordinates, ISIN and more), not every one of Wikidata's thousands of properties - `claimPropertyCount`
  tells you how many the entity has in total, and `wikidataUrl` links the full record.
- **A field is present only when the entity has that claim** - most items are not companies, so corporate
  fields (CEO, ISIN, revenue) are null for people, places and concepts. That is the data's shape.
- **Coverage and freshness follow Wikidata's community edits.**

### Pricing

**$0.001 per entity** on the FREE tier (tiered pricing lowers it with volume). Only entities actually
saved are billed; an empty search costs nothing.

### Output views

- **Entities** - Q-id, label, description, instance-of, country, website and Wikipedia link.

### Use with AI assistants (MCP)

Available through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - an agent can
resolve a company name to a canonical Q-id, enrich a list with country/industry/website, or disambiguate
entities in one call.

### Agent-ready: autonomous payments (x402 & Skyfire)

This actor is **agent-ready** - AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards:

- **[x402](https://docs.apify.com/platform/integrations/x402)** - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - no account, no API key.
- **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

# Actor input Schema

## `searchQueries` (type: `array`):

Names or terms to search Wikidata for, one per line - e.g. <code>Apify</code>, <code>Tesla</code>, <code>Marie Curie</code>. Each resolves to the matching entities. <b>Leave empty and the run returns a small free sample.</b>

## `entityIds` (type: `array`):

Specific Wikidata item ids to fetch exactly, one per line - e.g. <code>Q42</code>, <code>Q95</code>. A full entity URL also works.

## `language` (type: `string`):

Language code for labels/descriptions - e.g. <code>en</code>, <code>de</code>, <code>fr</code>. Falls back to English when a label is missing.

## `searchQueriesFromFile` (type: `string`):

Bulk-load search terms or Q-ids (auto-detected). Either <b>paste the whole list</b> (one per line), or give <b>a single link</b> to a public <code>.txt</code>/<code>.csv</code>, a Google Sheet/Drive link, or an Apify key-value-store record. A file that cannot be read says so and charges nothing.

## `maxItemsPerQuery` (type: `integer`):

How many matching entities to resolve for each search term.

## `maxItems` (type: `integer`):

Overall cap across all searches and Q-ids. You are only charged for entities actually saved.

## `outputFields` (type: `array`):

Pick the fields you want and every record is trimmed to exactly those - handy for lean CSV/Sheets exports.

## Actor input object example

```json
{
  "searchQueries": [
    "Apify"
  ],
  "language": "en",
  "maxItemsPerQuery": 25,
  "maxItems": 1000
}
```

# Actor output Schema

## `results` (type: `string`):

Each scraped record - a Wikidata entity with labels, claims and the Wikipedia link - as a JSON item in the default dataset.

# 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 = {
    "searchQueries": [
        "Apify"
    ],
    "language": "en",
    "searchQueriesFromFile": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/wikidata-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQueries": ["Apify"],
    "language": "en",
    "searchQueriesFromFile": "",
}

# Run the Actor and wait for it to finish
run = client.actor("scrapesage/wikidata-scraper").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 '{
  "searchQueries": [
    "Apify"
  ],
  "language": "en",
  "searchQueriesFromFile": ""
}' |
apify call scrapesage/wikidata-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesage/wikidata-scraper"
        }
    }
}

```

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/Rm08NYNOpg9TOqqOb/builds/fvV7tkeD0hyYVU9qQ/openapi.json