# Company Name to Website Finder: LEI & CIK (`infocomp/wikidata-company-finder`) Actor

Company name to website finder and enrichment from Wikidata (CC0): HQ, employees, industry, parent, ticker, LEI and SEC CIK for notable companies, or find by industry and country. Firm-level only; weak for small businesses. $2/1,000 rows. Not affiliated with Wikidata.

- **URL**: https://apify.com/infocomp/wikidata-company-finder.md
- **Developed by:** [InfoComp Data](https://apify.com/infocomp) (community)
- **Categories:** Lead generation, Business, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 company rows

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Company Name to Website Finder & Enrichment | Business Leads

**Turn a list of company names into official websites, HQ city and country, employees, founded year, industry, parent company, stock ticker and exchange, LEI and SEC CIK.** Or go the other way and **find notable companies** by industry, country, founded year, employee count or stock-exchange listing. Every row is one company with a **match type and a confidence score**, so you can judge each match.

All data is **Wikidata structured data (CC0, public domain)**, read from the official Wikidata Query Service. No API key, no login, no scraping, no Wikipedia article text and no logos or images.

> **Be clear about coverage.** Wikidata covers **notable and larger companies** (listed companies, big private firms, well-known startups and brands) very well and **small local businesses poorly or not at all**. If you need a plumber in Denver, use a business registry instead (see "Related tools"). If you need to clean up a list of recognisable company names, this tool is built for that.

**Firm-level only.** No CEO, founder, owner or any other person's name, no phone numbers, no emails and no street addresses are ever requested or returned.

### Two modes

| Mode | Use it to | You give | You get |
|---|---|---|---|
| **Enrich** (`"mode": "enrich"`) | Name to website, LEI and CIK. Clean up a company list. | `companyNames`, `domains` and/or `companies` (name + domain pairs), up to 300 per run | One row per matched company, plus `matchedQuery`, `matchType`, `matchConfidence`. Names that are **not found are free** and are listed in the run's `OUTPUT` record. |
| **Find** (`"mode": "find"`, default) | Build a list of notable companies. | Industries, countries (ISO codes), founded year range, minimum employees, listed-only, minimum notability | The most notable matching companies first (up to 500 per run). |

### What's in each row?

| Field | Meaning |
|---|---|
| `companyName`, `wikidataId`, `wikidataUrl` | Company name and its Wikidata item (e.g. `Q312`). |
| `website`, `domain` | Official website from Wikidata (preferred value, else the shortest current URL) and its host without `www`. |
| `city`, `country`, `countryCode`, `countryCodes` | Headquarters place as listed in Wikidata (if the HQ is a building, the place it is located in) and country. `countryCodes` lists every country Wikidata gives for the company. |
| `employees`, `employeesYear` | Latest employee count in Wikidata and the year it refers to. |
| `foundedYear` | Year of inception. |
| `industries` | Industry labels from Wikidata (up to 6). They are community-entered and can be broad or odd. |
| `parentOrganization` | Current parent organization, if any. |
| `tickerSymbol`, `stockExchange`, `listings` | Main stock listing (home-country exchange preferred) and all listings Wikidata knows. |
| `lei` | Legal Entity Identifier. |
| `cik`, `cikPadded` | **SEC Central Index Key**, without and with leading zeros. `cik` matches the `cik` field of **Form D Funding Leads**, so you can join the two. |
| `mode`, `matchedQuery`, `inputDomain` | Which mode produced the row and, in enrich mode, the name or domain you sent. |
| `matchType`, `matchConfidence`, `candidateCount`, `alternativeWikidataIds`, `domainMatch` | How the company was matched (see below). In find mode `matchType` is `filter` and the confidence is empty. |
| `wikidataSitelinks` | Number of Wikimedia pages linked to the item (a count only). A rough notability signal. |
| `dissolved` | `true` if Wikidata has a dissolved/abolished date (such companies are skipped unless you ask for them). |
| `source`, `sourceUrl`, `license`, `disclaimer`, `retrievedAt` | Credit to Wikidata (CC0), link to the item, license, a short disclaimer and the retrieval time. |

`companyName`, `city`, `country`, `cik`, `source`, `sourceUrl` and `retrievedAt` use the same names as the other InfoComp Business Leads tools, so outputs are easy to combine.

#### How matching works (enrich mode)

The name you send is compared with Wikidata **English labels and aliases** (exact text, then tolerant of case, a legal suffix such as Inc / Ltd / AG, `&` versus `and`). A domain is compared with the **official website** values (http/https, with or without `www`). Candidates must be real company-like items (not people, places or products): they need at least an identifier, industry, employee count, parent, legal form or a website with an HQ or founding date.

| `matchType` | Meaning | Base confidence |
|---|---|---|
| `name_and_domain` | Name and domain agree | 0.99 |
| `domain` | Official website equals your domain | 0.97 |
| `exact_label` / `exact_alias` | Name equals the Wikidata label / an alias | 0.90 / 0.80 |
| `normalized_label` / `normalized_alias` | Matched after case, suffix or `&` normalisation | 0.70 / 0.60 |

`matchConfidence` starts from that base and is **lowered when several companies share the name and none is clearly the most notable** (`candidateCount` tells you how many, `alternativeWikidataIds` lists the runners-up). It is a **heuristic, not a probability**. For ambiguous names send the domain as well.

Accents matter: Wikidata spells it "Nestlé", so "Nestle" is **not** found (and not charged). Use the official spelling.

### Pricing

**$2.00 per 1,000 company rows.** One `Company row` event ($0.002) per saved row. There is no start fee and no run fee. **Names that are not found, empty results, duplicates and failed runs are free.** If you set a maximum cost per run, the Actor stops cleanly when it is reached.

| Rows | Price |
|---|---|
| 20 (default run) | $0.04 |
| 100 | $0.20 |
| 1,000 | $2.00 |

### Input

```json
{
  "mode": "enrich",
  "companyNames": ["Tesla", "Siemens", "the coca-cola company"],
  "domains": ["shopify.com"],
  "companies": [{"name": "SAP", "domain": "sap.com"}]
}
```

```json
{
  "mode": "find",
  "industries": ["banking", "insurance"],
  "countries": ["DE", "FR"],
  "minEmployees": 5000,
  "listedOnly": true,
  "maxResults": 50
}
```

| Field | Default | What it does |
|---|---|---|
| `mode` | `find` | `find` or `enrich`. |
| `companyNames`, `domains`, `companies` | empty | Enrich mode. Up to 300 lookups per run (duplicates removed). |
| `industries` | empty | Find mode. 32 industry groups (software, banking, automotive, pharma ...); sub-industries in Wikidata are included. |
| `industryWikidataIds` | empty | Find mode, advanced: exact Wikidata industry items such as `Q880371`. |
| `countries` | empty | Find mode. ISO codes (`US`, `GB`, `DE`). Matches the company's country or HQ country. |
| `minEmployees`, `foundedFrom`, `foundedTo`, `listedOnly` | none | Find mode filters on the latest employee count, founding year and stock listing. |
| `minSitelinks` | 3 | Find mode notability floor. Lower it (0 to 2) to reach smaller companies; there are far fewer of them in Wikidata. |
| `requireWebsite` | true | Skip companies without an official website. |
| `includeDefunct` | false | Include companies with a dissolved date. |
| `maxResults` | 20 | Stop after this many rows (max 500). |

With **no input at all** the Actor runs a demo: the 20 most notable software companies in the United States.

A run summary (counts, filters, timing, query-service stats and, in enrich mode, every lookup that was not charged with its reason) is saved as `OUTPUT` (also `RUN_SUMMARY`) in the key-value store.

### Output examples

Real rows from local test runs on Nov 3, 2026 (not trimmed).

**Find mode** (default input, one of 20 rows):

```json
{
  "companyName": "Adobe",
  "wikidataId": "Q11463",
  "wikidataUrl": "https://www.wikidata.org/wiki/Q11463",
  "website": "https://www.adobe.com/",
  "domain": "adobe.com",
  "city": "San Jose",
  "country": "United States",
  "countryCode": "US",
  "countryCodes": [
    "US"
  ],
  "employees": 25988,
  "employeesYear": 2021,
  "foundedYear": 1982,
  "industries": [
    "AI",
    "artificial intelligence",
    "information technology",
    "software development",
    "software industry"
  ],
  "parentOrganization": null,
  "tickerSymbol": "ADBE",
  "stockExchange": "Nasdaq",
  "listings": [
    {
      "exchange": "London Stock Exchange",
      "ticker": "ABS"
    },
    {
      "exchange": "Nasdaq",
      "ticker": "ADBE"
    }
  ],
  "lei": "FU4LY2G4933NH2E1CP29",
  "cik": "796343",
  "cikPadded": "0000796343",
  "mode": "find",
  "matchedQuery": null,
  "inputDomain": null,
  "matchType": "filter",
  "matchConfidence": null,
  "domainMatch": null,
  "candidateCount": null,
  "alternativeWikidataIds": [],
  "wikidataSitelinks": 87,
  "dissolved": false,
  "source": "Wikidata (https://www.wikidata.org), structured data released under CC0 1.0 (public domain), queried through the Wikidata Query Service (query.wikidata.org).",
  "sourceUrl": "https://www.wikidata.org/wiki/Q11463",
  "license": "CC0 1.0 (Wikidata structured data)",
  "disclaimer": "Data comes from Wikidata (CC0) and is community-edited: it can be wrong, out of date or missing. Coverage focuses on notable, larger companies. Not affiliated with or endorsed by Wikidata or the Wikimedia Foundation.",
  "retrievedAt": "2026-11-03T20:39:20Z"
}
```

**Enrich mode** (`{"name": "Siemens", "domain": "siemens.com"}`):

```json
{
  "companyName": "Siemens",
  "wikidataId": "Q81230",
  "wikidataUrl": "https://www.wikidata.org/wiki/Q81230",
  "website": "https://www.siemens.com/",
  "domain": "siemens.com",
  "city": "Berlin",
  "country": "Germany",
  "countryCode": "DE",
  "countryCodes": [
    "DE"
  ],
  "employees": 320000,
  "employeesYear": 2023,
  "foundedYear": 1847,
  "industries": [
    "biomedical engineering",
    "electrical engineering",
    "electrical industry",
    "electronics industry",
    "lighting technique",
    "mechanical engineering"
  ],
  "parentOrganization": null,
  "tickerSymbol": "SIE",
  "stockExchange": "Frankfurt Stock Exchange",
  "listings": [
    {
      "exchange": "Frankfurt Stock Exchange",
      "ticker": "SIE"
    },
    {
      "exchange": "Frankfurter Wertpapierbörse",
      "ticker": "SIE"
    }
  ],
  "lei": "529900ZZVLZ93I1AW009",
  "cik": null,
  "cikPadded": null,
  "mode": "enrich",
  "matchedQuery": "Siemens",
  "inputDomain": "siemens.com",
  "matchType": "name_and_domain",
  "matchConfidence": 0.89,
  "domainMatch": true,
  "candidateCount": 3,
  "alternativeWikidataIds": [
    "Q12054212",
    "Q28970984"
  ],
  "wikidataSitelinks": 79,
  "dissolved": false,
  "source": "Wikidata (https://www.wikidata.org), structured data released under CC0 1.0 (public domain), queried through the Wikidata Query Service (query.wikidata.org).",
  "sourceUrl": "https://www.wikidata.org/wiki/Q81230",
  "license": "CC0 1.0 (Wikidata structured data)",
  "disclaimer": "Data comes from Wikidata (CC0) and is community-edited: it can be wrong, out of date or missing. Coverage focuses on notable, larger companies. Not affiliated with or endorsed by Wikidata or the Wikimedia Foundation.",
  "retrievedAt": "2026-11-03T20:39:41Z"
}
```

### Performance

Local runs on Nov 3, 2026 (about 2:25 to 2:45 PM Central), the default input (20 rows): **3.7 to 23.1 seconds** of Actor time over 10 runs (median about 7 s), always with **2 SPARQL queries** and about **73 MB** of memory. The spread is the Wikidata Query Service's response time (a query it has not seen recently can take 15 to 20 seconds), not our code. An enrich run of 21 lookups (16 companies found, 5 not found and not charged) took 3.6 to 13.6 seconds with 3 queries. A 300-row find run took 35 seconds. Default memory is 256 MB.

### Good to know

- **Coverage:** notable and larger companies. Small and local businesses are mostly missing, and many entries lack employees, LEI or CIK. Expect gaps.
- **Quality:** Wikidata is community-edited. Values can be outdated or wrong (for example an old employee count, or an acquired company still listed). Check what matters before you rely on it. `employeesYear` shows how old a count is.
- **Industries** use Wikidata's own labels and can be broad or unusual.
- **Several websites / exchanges:** we pick the preferred or shortest website and a home-market ticker; `listings` has the rest.
- **Politeness:** one run makes only 2 to 4 requests to the Wikidata Query Service, one at a time, with a descriptive User-Agent, and backs off on HTTP 429/5xx. If the service is overloaded the run fails cleanly and nothing is charged.

### Related InfoComp tools

- [SEC Form D Leads: New Startup Private Raise Filings](https://apify.com/infocomp/form-d-funding-leads): companies that just raised private capital, from public SEC EDGAR Form D filings.
- [Colorado New Business Filings: LLC & Corp Leads](https://apify.com/infocomp/new-business-filings-colorado): newly registered Colorado LLCs, corporations and nonprofits from the State's public open data.
- [FMCSA New MC Authority Leads: Carriers & Brokers](https://apify.com/infocomp/fmcsa-new-carrier-leads): trucking companies, freight brokers and forwarders whose FMCSA operating authority was just granted.
- [FMCSA USDOT Carrier Vetting: Authority & Insurance](https://apify.com/infocomp/fmcsa-carrier-vetting): bulk-check USDOT numbers: operating authority, insurance on file, safety flags and change alerts from FMCSA public data.
- [FDA Device Establishment Leads via openFDA](https://apify.com/infocomp/fda-device-establishment-leads): medical device makers, contract manufacturers and sterilizers from FDA registration data via openFDA.
- [OIG LEIE Exclusion & Medicare Opt-Out NPI Screen](https://apify.com/infocomp/oig-exclusion-optout-screen): bulk-check NPIs against the HHS-OIG LEIE file and the CMS Medicare opt-out list.
- [SAM.gov RFP Feed: Federal Contract Opportunities](https://apify.com/infocomp/sam-gov-opportunities): US federal contract opportunities (RFPs, solicitations, awards) from official SAM.gov public data.
- [EU TED & UK Tender Feed: Find a Tender Notices](https://apify.com/infocomp/eu-uk-tenders): EU and UK public tenders in one feed, from official TED, Find a Tender and Contracts Finder APIs.
- [Greenhouse Lever Ashby SmartRecruiters Jobs API](https://apify.com/infocomp/ats-jobs-feed): live job postings from Greenhouse, Lever, Ashby and SmartRecruiters via their official job-board APIs.
- [US Address Geocoder & FEMA Flood Zone Risk API](https://apify.com/infocomp/us-address-risk-enricher): batch-geocode US addresses with the Census Bureau and add FEMA flood zone and National Risk Index ratings.
- [NHTSA Bulk VIN Decoder: Specs, Recalls & MPG](https://apify.com/infocomp/bulk-vin-decoder-recalls-mpg): decode VINs in bulk with NHTSA vPIC, plus recall campaigns and EPA fuel economy.
- [arXiv PubMed Crossref OpenAlex Paper Search](https://apify.com/infocomp/scholarly-paper-search): search arXiv, PubMed, Crossref and OpenAlex in one run via official APIs, de-duplicated by DOI.
- [CMS Home Health Hospice Dialysis Facility Leads](https://apify.com/infocomp/cms-facility-leads): Medicare-certified home health agencies, hospices and dialysis centers from CMS open data, facility-level.
- [HUD Multifamily Property Manager Leads Section 8](https://apify.com/infocomp/hud-multifamily-leads): HUD-assisted apartment properties with management company, firm phone, Section 8 contract expiry and REAC score.
- [FDA 510(k) Clearance Leads: New Device Decisions](https://apify.com/infocomp/fda-510k-clearance-leads): companies that just got a medical device cleared by FDA: new 510(k) decisions from openFDA.

### Source, terms and disclaimer

- **Source:** [Wikidata](https://www.wikidata.org), queried through the [Wikidata Query Service](https://query.wikidata.org). Wikidata's structured data (items and properties) is released under **CC0 1.0** (public domain): https://www.wikidata.org/wiki/Wikidata:Licensing. We credit Wikidata in every row.
- **Not affiliated with or endorsed by** Wikidata, Wikimedia Deutschland or the Wikimedia Foundation. "Wikidata" and "Wikimedia" are their trademarks; we use the names only to name the data source and show no logos.
- The Actor follows the Wikimedia User-Agent policy and the Query Service limits (60 second query limit, polite request rate). See the User-Agent policy: https://foundation.wikimedia.org/wiki/Policy:User-Agent_policy.
- Found a wrong value? Every row has a `wikidataUrl`: the fix belongs in Wikidata itself (anyone can edit it), and the Wikidata community also runs a [Mismatch Finder](https://www.wikidata.org/wiki/Wikidata:Mismatch_Finder) for reporting data issues.
- Data is provided as is, with no warranty. It can be incomplete or out of date. Use it in line with your own legal and marketing obligations.

### FAQ

**Is this the official source for company websites or identifiers?** No. It is an independent tool that reads Wikidata. For legal identity use the LEI registry (GLEIF) and SEC EDGAR directly.

**Does it find small businesses?** Rarely. Wikidata is weak for small businesses. For new local companies use [New Business Filings Leads: Colorado](https://apify.com/infocomp/new-business-filings-colorado).

**Does it return executives, founders, emails or phone numbers?** No. By design it is firm-level only.

**Why was my name not found?** The spelling or accents differ from Wikidata's label, the company is not in Wikidata, or it has no company-like data. Try the official name, add the website domain, or check the `unmatched` list in `OUTPUT`.

# Actor input Schema

## `mode` (type: `string`):

Find = list notable companies that match your filters. Enrich = look up the companies you give in "Company names" / "Domains" / "Companies" and return website, HQ, employees, founded year, industry, parent, ticker, LEI and SEC CIK.

## `companyNames` (type: `array`):

Enrich mode. One company name per line, e.g. "Tesla" or "Siemens AG". Matching uses Wikidata English labels and aliases and tolerates case and legal suffixes (Inc, Ltd, ...). Max 300 companies per run.

## `domains` (type: `array`):

Enrich mode. Optional. One website per line, e.g. "shopify.com", to find the company whose official website in Wikidata is that domain.

## `companies` (type: `array`):

Enrich mode. Optional JSON list such as \[{"name": "Siemens", "domain": "siemens.com"}]. Giving both name and domain raises match confidence when they agree.

## `industries` (type: `array`):

Find mode. Companies whose Wikidata "industry" is one of these (sub-industries included). Empty = no industry filter. If industries, countries and Wikidata ids are all empty, a demo run uses Software in the United States.

## `industryWikidataIds` (type: `array`):

Find mode. Optional advanced filter: Wikidata item ids of industries, e.g. Q880371 (software industry). Only companies listing exactly that industry item are matched.

## `countries` (type: `array`):

Find mode. Two-letter ISO 3166-1 country codes such as US, GB, DE, IN. A company matches when its country or its headquarters country is one of them. Max 30.

## `minEmployees` (type: `integer`):

Find mode. Optional. Keep companies whose latest employee count in Wikidata is at least this. Companies without an employee count are dropped when this is set.

## `foundedFrom` (type: `integer`):

Find mode. Optional. Earliest founding (inception) year.

## `foundedTo` (type: `integer`):

Find mode. Optional. Latest founding (inception) year.

## `listedOnly` (type: `boolean`):

Find mode. Keep only companies with a stock exchange listing or ticker in Wikidata.

## `requireWebsite` (type: `boolean`):

Skip companies that have no official website in Wikidata (rows without a website are less useful as leads).

## `includeDefunct` (type: `boolean`):

By default companies with a "dissolved or abolished" date in Wikidata are skipped.

## `minSitelinks` (type: `integer`):

Find mode. A notability floor: the number of Wikimedia project pages linked to the company's Wikidata item (a count only, no article text is used). Higher = only well-known companies. Lower it to reach smaller companies; there are far fewer of them.

## `maxResults` (type: `integer`):

Stop after this many saved company rows (each is one billed "Company" event, $0.002). Find mode returns the most notable companies first.

## Actor input object example

```json
{
  "mode": "find",
  "companyNames": [],
  "domains": [],
  "companies": [],
  "industries": [
    "software"
  ],
  "industryWikidataIds": [],
  "countries": [
    "US"
  ],
  "listedOnly": false,
  "requireWebsite": true,
  "includeDefunct": false,
  "minSitelinks": 3,
  "maxResults": 20
}
```

# Actor output Schema

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

No description

## `summary` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mode": "find",
    "industries": [
        "software"
    ],
    "countries": [
        "US"
    ],
    "maxResults": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("infocomp/wikidata-company-finder").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 = {
    "mode": "find",
    "industries": ["software"],
    "countries": ["US"],
    "maxResults": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("infocomp/wikidata-company-finder").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 '{
  "mode": "find",
  "industries": [
    "software"
  ],
  "countries": [
    "US"
  ],
  "maxResults": 20
}' |
apify call infocomp/wikidata-company-finder --silent --output-dataset

```

## MCP server setup

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

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/bup42xHGzfEhIygC1/builds/lV4YuCeqsp5AYkfnL/openapi.json