# Korean Company Data — Directors, Shareholders & Financials (`foxlabs/korean-company-data`) Actor

Look up any Korean listed company and get directors with exact shareholdings, full IFRS financial statements (3-year, consolidated+separate), and firmographics. Clean JSON for KYC, due diligence & supply-chain verification.

- **URL**: https://apify.com/foxlabs/korean-company-data.md
- **Developed by:** [Berkan Kaplan](https://apify.com/foxlabs) (community)
- **Categories:** Lead generation
- **Features:** Limited permissions
- **Stats:** 6 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $25.00 / 1,000 results

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

## Korea Company Data — OpenDART 🇰🇷

**foXLabs Asia-Pacific company-registry series:** [Singapore](https://apify.com/foxlabs/singapore-company-data) · [Thailand](https://apify.com/foxlabs/thailand-company-data) · [Vietnam](https://apify.com/foxlabs/vietnam-company-data) · [Taiwan](https://apify.com/foxlabs/taiwan-company-data) · [Australia](https://apify.com/foxlabs/australia-company-data) · [Israel](https://apify.com/foxlabs/israel-company-data)

🎉 Turn Korean OpenDART into clean, structured company data — no login, no API key, one row per entity, with the corporate registration number, status, industry, address and listing details.
Built for B2B sales, lead generation, KYB / compliance and market-research teams.

### 🔍 What is the Korea Company Data — and when should you use it?

Give this actor company names or Korean corporate registration numbers and it returns matching companies from the Korean OpenDART corporate disclosure registry — as clean, deduplicated rows you can filter, export or feed to an AI agent. Every run reads the source live.

**Use it when you need:** a Korean listed-company list for outreach; filed financials and executives for diligence; or a starting point for market research.

**Use something else when:** you need firmographics the registry doesn’t hold (revenue, headcount, website, email) — pair this with an enrichment actor from [Fox Labs](https://apify.com/foxlabs).

### 🤖 Use with AI agents

**Already on the Apify MCP server?** Ask for this Actor by name: `foxlabs/korean-company-data`.

**Your agent can pay for its own runs.** This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over **x402 (USDC on Base)** or **Skyfire** — no Apify account or API token of its own. Billing is the same either way: per delivered record, never for errors.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

```
I want to pull Korea company records using the Apify Actor `foxlabs/korean-company-data`.
Input: `stockCodes` is a list of Korean stock codes (e.g. `005930` for Samsung Electronics); `companyNames` and `corp_codes` are alternative ways in; `includeFinancials` adds the financial statements and `outputLanguage` chooses Korean, English or both.
Start with: {"stockCodes":["005930","000660"],"maxResults":100}
Ask me what to look up, run the Actor, then summarise the rows as a table.
```

The machine-readable API, MCP config and OpenAPI definition live at `apify.com/foxlabs/korean-company-data.md`.

### 📋 Overview

Everything you need to turn the Korean OpenDART corporate disclosure registry into clean, structured data — in one actor, with no login, cookies or API key.

**Why teams pick this actor:**

- ✅ **Whole registry, one call** — name or ID in, matching companies out.
- 🧹 **No empty-promise columns** — only fields this registry actually fills; degenerate columns are removed.
- 🔗 **Stable identifiers** — every row carries the source's own IDs, ready to join across runs and to other Fox Labs actors.
- 💰 **Per-row pricing** — a minimal price per delivered row, no subscription.
- 🤖 **Agent-ready** — MCP + x402 agentic payments.

### ✨ Features

- 🔍 **Name or ID lookup** — relevance-ranked name search or exact registry-ID lookup.
- 🏢 **Full entity profile** — status, legal form, formation date, address and the registry’s own contact fields.
- 🧹 **Clean schema** — deduplicated camelCase rows, ready for CSV/Excel/JSON.

### 🎬 Quick Start

```bash
curl -X POST "https://api.apify.com/v2/acts/foxlabs~korean-company-data/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"stockCodes":["005930","000660"],"maxResults":100}'
```

### 🚀 Getting Started (3 steps)

1. **Choose your targets** — company names or Korean corporate registration numbers.
2. **Set the cap** — `maxResults` limits how many companies are returned (default 100).
3. **Run and export** — get a clean dataset as JSON, CSV or Excel.

### 📥 Input

```json
{"stockCodes":["005930","000660"],"maxResults":100}
```

| Field | Type | Description |
|---|---|---|
| `stockCodes` | array | Korean stock codes, e.g. `005930` (Samsung Electronics), `000660` (SK Hynix). |
| `corp_codes` | array | DART corporation codes, if you already have them. |
| `companyNames` | array | Company names to resolve to a DART record. |
| `industryCode` | string | Optional industry filter. |
| `includeFinancials` | boolean | Also fetch the filed financial statements (default on). |
| `maxExecutivesPerCompany` | integer | Cap on executives returned per company (default 100). |
| `outputLanguage` | string | `ko`, `en` or `both` (default `both`). |
| `maxResults` | integer | Most companies returned in one run (default 100). |
| `maxConcurrency` | integer | Requests in parallel (default 5). |
| `crtfc_key` | string | Optional own OpenDART API key; leave empty to use the built-in key. |

### 📤 Output

One row per company, saved to the dataset. Every row carries `scrapedAt`. Lookups that cannot be completed are reported in the run log and in the `FAILED_LOOKUPS` record in the key-value store — they are not written to the dataset, so they are not charged.

| Field | Description |
|---|---|
| `corp_code` | Corp_code |
| `corp_name` | Corp_name |
| `corp_name_eng` | Corp_name_eng |
| `stock_code` | Stock_code |
| `stock_name` | Stock_name |
| `is_listed` | Is_listed |
| `ceo` | Ceo |
| `ceo_romanized` | Ceo_romanized |
| `bizr_no` | Bizr_no |
| `jurir_no` | Jurir_no |
| `address` | Principal address |
| `address_romanized` | Address_romanized |
| `website` | Website |
| `phone` | Phone |
| `fax` | Fax |
| `industry_code` | Industry_code |
| `industry_desc` | Industry_desc |
| `established_date` | Established_date |
| `fiscal_month` | Fiscal_month |
| `total_issued_shares` | Total_issued_shares |
| `total_issued_shares_class` | Total_issued_shares_class |
| `total_issued_shares_as_of` | Total_issued_shares_as_of |
| `executives` | Executives |
| `executives_count` | Executives_count |
| `executive_filings_count` | Executive_filings_count |
| `executives_text` | Executives_text |
| `financials` | Financials |
| `financials_text` | Financials_text |
| `matched` | Matched |
| `resolvedFrom` | Resolved From |
| `resolvedFromType` | Resolved From Type |
| `source` | Source |
| `source_url` | Source_url |
| `scraped_at` | Scraped_at |

### 💼 Use cases

**1. Korea B2B lead lists** — Korean companies by name or industry.
*Input:* name searches. *Output:* entities + industry + address. *Use:* a ready list.

**2. Firmographic enrichment** — attach industry and listing details to a company.
*Input:* registration numbers. *Output:* the OpenDART record. *Use:* enrich a CRM.

**3. KYB / due diligence** — verify a Korean company by registration number.
*Input:* the number or name. *Output:* the canonical OpenDART record. *Use:* confirm existence and status.

### 🔗 Integration

**JavaScript / Node.js**

```javascript
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/korean-company-data').call({"stockCodes":["005930","000660"],"maxResults":100});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);
```

**Python**

```python
from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/korean-company-data').call(run_input={"stockCodes":["005930","000660"],"maxResults":100})
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)
```

Written for `apify-client` 3 for Python, where `call()` returns a run object; with version 1 or 2 it returns a dict — write `run['defaultDatasetId']` there.

**Automation (n8n / Zapier / Make):** schedule or webhook → HTTP request to the actor API with your input list → handle the JSON dataset → push to a sheet, CRM or dashboard.

### 📊 Pricing

Pay-per-event: **per row written to the dataset**. Lookups that fail are not written to the dataset — they go to the run log and the `FAILED_LOOKUPS` record in the key-value store — so they are never charged.

### ❓ FAQ

**Do I need an account, login or API key?** No. This reads the Korean OpenDART corporate disclosure registry.

**What do I search by?** Company names or Korean corporate registration numbers.

**How current is the data?** Every run reads the Korean OpenDART corporate disclosure registry live, so results are as current as the source.

**Why are firmographics like revenue or website missing?** A public business registry doesn’t hold them; we don’t ship empty columns. Pair with an enrichment actor from Fox Labs.

**Can I export to CSV / Excel / JSON?** Yes — directly from the Apify dataset.

### 🐛 Troubleshooting

- **Fewer rows than expected** — raise `maxResults`, or refine the input.
- **A name returns an unexpected entity** — it matched a similar registered name; search the exact registry ID.
- **No rows for a name** — try the entity’s exact legal name or its registry ID.

### ⚖️ Is it legal to scrape this data?

This actor reads a public government business registry published as open data. Results can still contain personal data (e.g. a registered agent’s name); personal data is protected by the GDPR and similar laws, so only process it with a legitimate basis. See Apify’s blog post on the legality of web scraping.

### 🤝 Support & contact

- 🌐 **Website:** [data.foxlabs.com.tr](https://data.foxlabs.com.tr)
- 📧 **Email:** info@foxlabs.com.tr
- 🐛 **Issues:** open a ticket in the Actor’s **Issues** tab
- 🧰 **More clean B2B data actors:** [Fox Labs on Apify](https://apify.com/foxlabs)

### Changelog

#### 0.1.29 — 2026-10-08 — README: the Python example works with the current Apify client

- The README's Python example read the results with `run['defaultDatasetId']`. With the current Apify client for Python (version 3) `call()` returns a run object, not a dict, and that line raised `TypeError: 'Run' object is not subscriptable` — after the run itself had finished. The example now reads `run.default_dataset_id`; with client version 1 or 2, keep `run['defaultDatasetId']`. Checked with apify-client 3.2.1, 2.5.1 and 1.12.2.
- No code, output field or pricing change.

#### 0.1.28 — 2026-09-20 — README corrected against the real input schema

- **Every code example was broken.** The AI-agent, cURL, JavaScript and Python examples used keys that do not exist in this Actor's input schema (`queries`, `maxResultsPerQuery`) with a literal placeholder string instead of a real value, and the input table listed those phantom fields instead of the real ones. Anyone who copied an example got a failing run. All examples now match the schema prefill exactly.
- **Removed promises the Actor does not keep:** "formation / status monitoring", "a canonical registry record for KYB and due diligence", and "every row carries `query`" (there is no `query` field). Fixed a duplicated word in the intro.
- **Billing wording corrected.** The README said "empty/failed lookups are never billed" without saying why. Failed lookups are not written to the dataset at all — they are reported in the run log and in the `FAILED_LOOKUPS` record in the key-value store — so there is no row to charge. Stated plainly instead of implied.
- No code, output field or pricing change.

#### 0.5 — 2026-09-10 — hotfix

- Builds 0.1.24–0.1.25 shipped a corrupted bundled company index, so every run since 2026-09-07 failed (exit 91). Restored the valid 118K index and fixed the live-download fallback (it aborted on a null proxy setting).

#### 0.1 — 2026-09-07

- **Enabled AI-agent payments (x402) + rebuilt the README to the full standard** (What-is / when, AI-agents + x402 agentic payments + MCP, Overview, Features, Use cases, Integration, FAQ, Troubleshooting, Support & contact).

#### 0.0

- Initial release: data from the Korean OpenDART corporate disclosure registry by name or registry ID.

# Changelog

This Actor's version history is a separate document: https://apify.com/foxlabs/korean-company-data/changelog.md

# Actor input Schema

## `stockCodes` (type: `array`):

6-digit Korea Exchange ticker codes — one per line (e.g. 005930 = Samsung Electronics, 000660 = SK hynix). Auto-resolved to a DART corp code.

## `corp_codes` (type: `array`):

8-digit DART internal corporate codes — the fastest, exact lookup (e.g. 00126380 = Samsung Electronics).

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

Korean or English company names — one per line. Resolved against the 118K DART index; ambiguous names use the first match, so prefer stock or corp codes for precision.

## `industryCode` (type: `string`):

Optional. Scan LISTED (KOSPI/KOSDAQ) companies and keep those whose KSIC industry code starts with this sector prefix. API-intensive and slower — pair it with Max companies. Leave as 'none' to look up by code/name instead.

## `includeFinancials` (type: `boolean`):

Attach the most recent ANNUAL IFRS statements (balance sheet + income statement, 3-year, consolidated CFS + separate OFS). Adds one API call per company.

## `maxExecutivesPerCompany` (type: `integer`):

Cap the executive list per company (registered directors first, then by shares held). 0 = return all.

## `outputLanguage` (type: `string`):

How names, addresses and titles are presented. 'Both' keeps Korean and adds Romanized/English. 'English' makes Romanized/English primary and moves Korean to \*\_ko fields.

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

Hard cap on the number of company records returned. 0 = unlimited.

## `maxConcurrency` (type: `integer`):

Number of parallel OpenDART fetches. Higher = faster but more likely to hit rate limits (auto-retried). Default 5.

## `crtfc_key` (type: `string`):

Optional. Your own free OpenDART key (opendart.fss.or.kr) for higher rate limits. Leave blank to use the built-in shared key.

## Actor input object example

```json
{
  "stockCodes": [
    "005930",
    "000660"
  ],
  "corp_codes": [],
  "companyNames": [],
  "industryCode": "",
  "includeFinancials": true,
  "maxExecutivesPerCompany": 100,
  "outputLanguage": "both",
  "maxResults": 100,
  "maxConcurrency": 5
}
```

# Actor output Schema

## `dataset` (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 = {
    "stockCodes": [
        "005930",
        "000660"
    ],
    "corp_codes": [],
    "companyNames": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("foxlabs/korean-company-data").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 = {
    "stockCodes": [
        "005930",
        "000660",
    ],
    "corp_codes": [],
    "companyNames": [],
}

# Run the Actor and wait for it to finish
run = client.actor("foxlabs/korean-company-data").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 '{
  "stockCodes": [
    "005930",
    "000660"
  ],
  "corp_codes": [],
  "companyNames": []
}' |
apify call foxlabs/korean-company-data --silent --output-dataset

```

## MCP server setup

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

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/ETBQ9uaxiOLHVHGzo/builds/lVH2txiXHTrFr7vm2/openapi.json