# Naver Blog & Cafe Scraper — Korean Word-of-Mouth Search (`kdatafactory/naver-blog-cafe-scraper`) Actor

Search Naver Blog (네이버 블로그) and Naver Cafe (네이버 카페) by keyword and get posts as clean JSON: title, snippet, author, blog/cafe name, post URL, publish date and thumbnail. Korea's word-of-mouth layer, for brand monitoring and PR tracking.

- **URL**: https://apify.com/kdatafactory/naver-blog-cafe-scraper.md
- **Developed by:** [Seok June Park](https://apify.com/kdatafactory) (community)
- **Categories:** Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 posts

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/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 Blog & Cafe Scraper — Korea's Word-of-Mouth Layer

Search **Naver Blog (네이버 블로그)** and **Naver Cafe (네이버 카페)** by keyword and get posts back as clean JSON/CSV: title, snippet, author, blog/cafe name, post URL, publish date and thumbnail.

> **Why this matters.** In Korea, brand conversation does not happen on Twitter or Reddit — it happens on Naver blogs and in Naver cafes (community forums). If you are tracking a brand, a product launch, a restaurant or a neighbourhood in Korea, this is the layer where people actually talk.

### What you get

One row per post:

| Field | Meaning |
|---|---|
| `source` | `naver_blog` or `naver_cafe` |
| `keyword`, `rank` | The search term, and the post's position in those results |
| `title`, `snippet` | Post title and the matched excerpt (search highlight markup stripped) |
| `author` | Blogger pen name (blog only — the cafe tab shows the cafe, not the member) |
| `channel_name`, `channel_id` | Blog or cafe name, and its Naver ID |
| `posted_at` | Publish date (`YYYY-MM-DD`) |
| `is_sponsored` | `true` when Naver flags the post as a paid/sponsored placement |
| `url`, `thumbnail_url`, `post_id`, `scraped_at` | Canonical post link, thumbnail, id, KST timestamp |

### Input example

```json
{
  "keyword": "성수동 카페",
  "source": "both",
  "sort": "sim",
  "maxItems": 60
}
```

### Output example (real row)

```json
{
  "source": "naver_blog",
  "keyword": "성수동 카페",
  "rank": 1,
  "title": "[성수동 카페거리] 주말 웨이팅 필수 핫플레이스 동선과 주차 팁",
  "snippet": "주말마다 힙한 에너지와 세련된 팝업스토어로 발 디딜 틈이 없는 곳…",
  "author": "아파트럼프",
  "channel_name": "아파트과 부도",
  "channel_id": "10231sy",
  "posted_at": "2026-07-02",
  "url": "https://blog.naver.com/10231sy/224333861881"
}
```

### Coverage and honest limits

- **Blog** reads Naver's own blog-section search API. It reports the match count (commonly ~1,000 for a broad keyword) and paginates cleanly, so `maxItems` up to 1,000 is real.
- **Cafe** reads Naver's mobile cafe search tab, which serves about **30 posts per keyword** — Naver publishes no deeper public cafe search. Asking for more will not invent results.
- Naver shows a publish date on only **some** cafe cards, so `posted_at` is `null` for the rest. It is left null rather than guessed.
- `author` is blog-only by design: the cafe result card identifies the cafe, not the individual member.
- If a requested source returns nothing, the run **warns and records it** in an `EMPTY_SOURCES` key-value record instead of finishing quietly.

### Privacy

Only public search results are collected — no login, no private cafe content, no member profiles. `author` and `channel_name` are the public pen name and blog/cafe name Naver itself prints on the result card.

# Actor input Schema

## `keyword` (type: `string`):

The Korean (or English) term to search for — a brand, product, place or topic. Example: '성수동 카페', '올리브영 세일', 'Torriden'.

## `source` (type: `string`):

blog = Naver Blog only (deep, paginates to ~1,000 posts). cafe = Naver Cafe only (the mobile cafe tab, ~30 posts per keyword). both = split the item budget across the two.

## `sort` (type: `string`):

sim = relevance (Naver's default), date = newest first. Naver's cafe tab exposes no sort option, so this applies to the blog source only.

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

How many posts to collect. Naver's blog search tops out around 1,000 results per keyword; the cafe tab serves about 30.

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

Optional. Naver serves both sources to ordinary IPs, so a proxy is not required. Enable it for high-volume schedules.

## Actor input object example

```json
{
  "keyword": "성수동 카페",
  "source": "blog",
  "sort": "sim",
  "maxItems": 60,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

Every record collected in this run.

# 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 = {
    "keyword": "성수동 카페"
};

// Run the Actor and wait for it to finish
const run = await client.actor("kdatafactory/naver-blog-cafe-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 = { "keyword": "성수동 카페" }

# Run the Actor and wait for it to finish
run = client.actor("kdatafactory/naver-blog-cafe-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 '{
  "keyword": "성수동 카페"
}' |
apify call kdatafactory/naver-blog-cafe-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kdatafactory/naver-blog-cafe-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/XVlUV9MI8lgBAf5Xb/builds/kVFBcHmfCZrV2xx2W/openapi.json