# Naver Cafe Search Results Scraper (`searchapi/naver-cafe-search-scraper`) Actor

Scrapes Naver Cafe search results for any keyword. Extracts publicly visible cafe article metadata: title, URL, snippet, cafe name, date, thumbnail from search.naver.com cafe tab. Does NOT access private cafe posts.

- **URL**: https://apify.com/searchapi/naver-cafe-search-scraper.md
- **Developed by:** [Search API](https://apify.com/searchapi) (community)
- **Categories:** Automation, Developer tools, SEO tools
- **Stats:** 2 total users, 1 monthly users, 80.0% 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/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

## Naver Cafe Search Scraper

Collect public metadata from Naver's Cafe search tab. The Actor does not sign in, open private posts, or bypass Cafe membership controls. It reads only information that Naver exposes on the public search-results page: article title and canonical URL, snippet, Cafe identity, date label, thumbnail, ranking, query, and scrape provenance.

### Input

Use `query` for one search or `queries` for a batch. Duplicate and blank queries are removed. `maxItems` is a global output limit shared fairly across queries. `maxPages` limits traversal for every query, `maxConcurrency` bounds browser parallelism, and `maxRequestRetries` bounds retry cost. Direct access is the default QA configuration; an authorized Apify Proxy configuration can be supplied when the target blocks the execution environment.

```json
{
  "queries": ["인공지능", "로봇"],
  "maxItems": 20,
  "maxPages": 2,
  "maxConcurrency": 2,
  "proxyConfiguration": { "useApifyProxy": false }
}
```

### Output

Each dataset item is one public Cafe article search result. `id` is query-aware so the same article can legitimately appear for two requested queries, while `articleKey` remains stable across queries. `position` is global output order, `queryPosition` is rank within the query, and `page` records the Naver result page. `url` and `link` are canonical public article URLs with transient tracking tokens removed. `articleId` and `cafeSlug` are parsed from that URL. Optional source-backed fields are omitted rather than filled with guesses.

```json
{
  "id": "naver-cafe:example:123:q:%EC%9D%B8%EA%B3%B5%EC%A7%80%EB%8A%A5",
  "articleKey": "example:123",
  "articleId": "123",
  "cafeSlug": "example",
  "position": 1,
  "queryPosition": 1,
  "page": 1,
  "title": "Public Cafe article title",
  "url": "https://cafe.naver.com/example/123",
  "snippet": "Public search snippet",
  "cafeName": "Example Cafe",
  "cafeUrl": "https://cafe.naver.com/example",
  "dateRaw": "2일 전",
  "publishedAt": "2026-08-28T00:00:00.000Z",
  "query": "인공지능",
  "sourceDomain": "search.naver.com",
  "scrapedAt": "2026-08-30T00:00:00.000Z"
}
```

Relative Korean date labels are converted against scrape time and are approximate. The original label is preserved in `dateRaw`.

### Reliability and responsible use

The Actor uses Naver's current `ssc=tab.cafe.all` route and real page offsets, canonicalizes article identity, stops repeated result pages, checks HTTP/content type and visible challenge markers, and fails closed on selector drift. It never stores CAPTCHA or access-denial pages as data. Limits are reserved before asynchronous writes, preventing concurrent queries from exceeding `maxItems`.

Run locally with `apify run --purge --input-file qa-inputs/local-search.json`. Use `npm test`, `npm run check`, `apify validate-schema`, and `node validate-datasets.js` for verification. Website markup and access policy may change; keep request volumes modest and comply with Naver's terms, applicable law, and the privacy expectations of Cafe authors.

# Actor input Schema

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

One public Naver Cafe search query.

## `queries` (type: `array`):

Optional batch of queries. Combined with query and de-duplicated.

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

Global maximum number of records.

## `maxPages` (type: `integer`):

Maximum result pages visited for each query.

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

Maximum simultaneous browser pages.

## `maxRequestRetries` (type: `integer`):

Maximum retries for a failed page.

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

Optional authorized Apify Proxy settings.

## Actor input object example

```json
{
  "query": "인공지능",
  "maxItems": 50,
  "maxPages": 5,
  "maxConcurrency": 2,
  "maxRequestRetries": 2
}
```

# 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 = {
    "query": "인공지능"
};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/naver-cafe-search-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": "인공지능" }

# Run the Actor and wait for it to finish
run = client.actor("searchapi/naver-cafe-search-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": "인공지능"
}' |
apify call searchapi/naver-cafe-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,searchapi/naver-cafe-search-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/LErUZK8qAOiBcixQF/builds/MvgOukFomDUrpvjcl/openapi.json