# Naver Knowledge iN Scraper (`searchapi/naver-knowledge-in-scraper`) Actor

Scrapes public Q\&A from Naver Knowledge iN (지식iN) — Korea's largest Q\&A platform. Extracts question, answer, category, date, author, and view count via search.naver.com kin tab.

- **URL**: https://apify.com/searchapi/naver-knowledge-in-scraper.md
- **Developed by:** [Search API](https://apify.com/searchapi) (community)
- **Categories:** Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.99 / 1,000 search results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

## Naver Knowledge iN Scraper

Scrapes public Q\&A from Naver Knowledge iN (지식iN) — Korea's largest Q\&A platform. Extracts question, answer, category, date, author, and view count via search.naver.com kin tab.

### What this Actor collects

The Actor converts community discussions and Q\&A records into clean JSON records that can be downloaded, queried through the Apify API, or sent to downstream workflows.

- Uses the input limits and filters below to control the crawl.
- Stores source-backed fields defined by the 13-field dataset schema.
- Omits optional fields when the source does not expose a value instead of writing nulls or fabricated placeholders.

### Use cases

- Community and audience research
- Question and answer monitoring
- Discussion-source enrichment

### Input

Provide input in JSON. Fields marked required must be supplied; source-specific alternatives and constraints are described in the field text.

| Field | Type | Required | Default | Description |
| --- | --- | :---: | --- | --- |
| `query` | string | Yes | `"파이썬"` | The search term to look up on Naver Knowledge iN |
| `maxItems` | integer | No | `50` | Maximum number of Q\&A results to scrape |
| `proxyConfiguration` | object | No | — | Proxy settings for the scraper |

#### Example input

```json
{
  "query": "파이썬",
  "maxItems": 20
}
```

### Output

The default dataset contains one item per public Knowledge iN Q\&A result. The following are the most useful fields; availability can vary by source response.

| Field | Type | Description |
| --- | --- | --- |
| `position` | integer | Position |
| `title` | string | Question Title |
| `category` | string | Category |
| `author` | string | Author |
| `date` | string | Date |
| `answerCount` | integer | Answer Count |
| `query` | string | Search Query |
| `scrapedAt` | string | Scraped At |
| `snippet` | string | Question Snippet |
| `link` | string | Question URL |
| `searchQuery` | string | Normalized Search Query |
| `page` | integer | Result Page |
| `searchMetadata` | object | Search Metadata |

<details>
<summary>All 13 declared dataset fields</summary>

`position`, `title`, `link`, `snippet`, `category`, `author`, `date`, `answerCount`, `query`, `scrapedAt`
`searchQuery`, `page`, `searchMetadata`

</details>

#### Example dataset item

This compact example is taken from local Actor storage. Long text and nested collections are shortened for documentation only.

```json
{
  "position": 1,
  "title": "파이썬 따옴표",
  "author": "비공개",
  "date": "2024.10.29.",
  "answerCount": 0,
  "query": "파이썬",
  "scrapedAt": "2026-07-23T12:16:10.114Z",
  "snippet": "문자열을 '로 감싸는경우엔 \\' \"로 감싸는경우엔 \\\" >>> \"& \"& >>> \"\"&\" \"&",
  "link": "https://kin.naver.com/qna/detail.naver?answerNo=1&dirId=10402&docId=477246947&kinsrch_src=pc_tab_kin&qb=7YyM7J207I2s",
  "searchQuery": "파이썬",
  "page": 1,
  "searchMetadata": {
    "engine": "naver-knowledge-in",
    "page": 1,
    "query": "파이썬",
    "scrapedAt": "2026-07-23T12:16:10.114Z"
  }
}
```

### Related Actors

- [Naver Blog Search Scraper](https://apify.com/searchapi/naver-blog-search-scraper)
- [Naver Cafe Search Results Scraper](https://apify.com/searchapi/naver-cafe-search-scraper)
- [Naver DataLab Trends Scraper](https://apify.com/searchapi/naver-datalab-trends-scraper)

# Actor input Schema

## `query` (type: `string`):

The search term to look up on Naver Knowledge iN

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

Maximum number of Q\&A results to scrape

## `proxyConfiguration` (type: `object`):

Proxy settings for the scraper

## Actor input object example

```json
{
  "query": "서울 맛집",
  "maxItems": 50
}
```

# Actor output Schema

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

Dataset schema for naver-knowledge-in-scraper

# 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 = {
    "query": "파이썬"
};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/naver-knowledge-in-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 = { "query": "파이썬" }

# Run the Actor and wait for it to finish
run = client.actor("searchapi/naver-knowledge-in-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 '{
  "query": "파이썬"
}' |
apify call searchapi/naver-knowledge-in-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,searchapi/naver-knowledge-in-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/BbFdGNHzlmLg2uzme/builds/9stiHVReznorf9sOj/openapi.json