# Naver Map Places Scraper (`fetch_cat/naver-map-places-scraper`) Actor Extract public Naver Map business listings with addresses, phones, websites, coordinates, categories, review counts, and place URLs. - **URL**: https://apify.com/fetch\_cat/naver-map-places-scraper.md - **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.60 / 1,000 place saveds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 Map Places Scraper Extract public Naver Map business listings for Korea-focused local SEO, lead generation, market research, and territory planning. ### What does Naver Map Places Scraper do? Naver Map Places Scraper turns Naver Map search results into structured dataset rows. Use it to collect public place and business data from Korean local searches, including: - Business names - Categories - Addresses and road addresses - Phone numbers when available - Website links when available - Naver place URLs - Coordinates - Review counts - Business status hints - Image URLs and short descriptions when available The actor is designed for search-result extraction, so each saved row represents one public Naver Map place returned for your query. ### Who is it for? This actor is useful for teams that need Korea-specific local business data. - Local SEO agencies prospecting Korean businesses - Sales teams building lead lists by city or district - Market researchers comparing neighborhoods or categories - Expansion teams checking local competition before opening a branch - Data teams enriching internal business directories - Agencies monitoring listings for clients on Naver Map ### Why use this scraper? Naver is a key local discovery platform in South Korea. Manual research on Naver Map is slow when you need repeatable exports, comparisons, or scheduled monitoring. This actor helps you: - Run repeatable local searches - Export results as JSON, CSV, Excel, or via API - Schedule recurring checks in Apify - Connect data to CRMs, spreadsheets, dashboards, and enrichment workflows - Keep one consistent output structure across many Korean search terms ### How much does it cost to scrape Naver Map places? The actor uses pay-per-event pricing. - A small start charge is applied once per run. - A per-place charge is applied only for saved dataset rows. - Smaller test runs are inexpensive because you can limit results per query. - You can control cost by lowering `maxResultsPerQuery` and using focused queries. Start with 10 to 25 places per query, review the output, then scale up only after the data matches your workflow. ### Input overview Provide one or more Naver Map search terms. The most important fields are: - `queries` — search terms such as `카페`, `강남 맛집`, `부산 호텔`, or `서울 병원` - `location` — optional city, district, or neighborhood appended to each query - `maxResultsPerQuery` — maximum number of places saved for each query - `proxyConfiguration` — optional Apify Proxy settings if your environment is challenged ### Example input ```json { "queries": ["카페", "강남 맛집"], "location": "서울", "maxResultsPerQuery": 25, "includeDetails": true, "proxyConfiguration": { "useApifyProxy": false } } ```` ### Search examples Try focused searches first. - `카페` with location `서울` - `강남 맛집` - `부산 호텔` - `홍대 미용실` - `서울 병원` - `제주 렌터카` - `인천 치과` - `대구 네일샵` Korean keywords usually provide the broadest coverage. English keywords can work for some categories, but Korean search terms are recommended for local completeness. ### Output data Each dataset item is one Naver Map place. The actor returns public fields exposed in search results. Some fields may be null because not every listing publishes the same information. ### Data fields | Field | Description | | --- | --- | | `query` | Search query used for the result | | `rank` | Result rank within the query | | `placeId` | Naver place identifier | | `name` | Place or business name | | `category` | Primary category | | `categories` | Category list when available | | `address` | Address text | | `roadAddress` | Road address text | | `phone` | Public phone number when available | | `website` | Public website when available | | `naverUrl` | Naver Map place URL | | `latitude` | Latitude coordinate | | `longitude` | Longitude coordinate | | `rating` | Rating value when available | | `reviewCount` | Total review count when available | | `visitorReviewCount` | Visitor review count when available | | `blogReviewCount` | Blog review count when available | | `openingHours` | Opening-hours/status text when available | | `businessStatus` | Business status text when available | | `tags` | Search-result badges, context labels, or review snippets | | `placeDescription` | Short description when available | | `imageUrl` | Thumbnail image URL when available | | `menuInfo` | Menu summary when available | | `distanceMeters` | Distance value when available | | `scrapedAt` | ISO timestamp for the scrape | ### Example output item ```json { "query": "카페 서울", "rank": 1, "placeId": "2023348447", "name": "Example Cafe", "category": "카페,디저트", "categories": ["카페,디저트"], "address": "서울 중구 예시동 1", "roadAddress": "서울 중구 예시로 1", "phone": "0507-0000-0000", "website": "https://example.com", "naverUrl": "https://map.naver.com/p/entry/place/2023348447", "latitude": 37.5674, "longitude": 126.979, "rating": null, "reviewCount": 717, "visitorReviewCount": 650, "blogReviewCount": 67, "openingHours": "영업 중", "businessStatus": "영업 중", "tags": ["분위기 좋은", "디저트"], "placeDescription": "Public description text when available", "imageUrl": "https://example.com/image.jpg", "menuInfo": "Americano, Latte", "distanceMeters": 320, "scrapedAt": "2026-07-05T00:00:00.000Z" } ``` ### How to run on Apify 1. Open Naver Map Places Scraper on Apify. 2. Enter one or more search terms in `queries`. 3. Add a `location` hint if you want district-level results. 4. Set `maxResultsPerQuery` to a small value for the first run. 5. Start the actor. 6. Review the dataset sample. 7. Export results or connect them to your downstream workflow. ### Tips for better results - Use Korean keywords for better local coverage. - Add district names for more precise intent. - Prefer several focused searches over one broad search. - Keep first runs small while checking output quality. - Search by business type plus area, such as `치과 강남` or `호텔 부산`. - Review null fields before assuming a listing has no data; Naver may simply not expose that field in search results. ### Limits The actor currently saves up to 70 visible places per query. Very broad terms may have more total results on Naver Map, but this limit keeps runs predictable and affordable. If you need wider coverage, run multiple focused searches by district, neighborhood, or category. ### Proxy settings Start without proxy for the lowest cost. If Naver returns an anti-bot challenge from your environment, enable Apify Proxy and keep test inputs small. Recommended workflow: - First run: proxy disabled, 10 results per query - If challenged: enable Apify Proxy - If scaling: increase result limits gradually after confirming output quality ### Integrations Naver Map Places Scraper works well with common Apify integrations. - Export CSV files for sales teams. - Send rows to Google Sheets for manual review. - Trigger webhooks when a run finishes. - Sync results to a CRM as local-business leads. - Feed coordinates into BI dashboards or map visualizations. - Schedule recurring searches for local SEO monitoring. ### API usage with Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('fetch_cat/naver-map-places-scraper').call({ queries: ['카페'], location: '서울', maxResultsPerQuery: 10, includeDetails: true, proxyConfiguration: { useApifyProxy: false }, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### API usage with Python ```python from apify_client import ApifyClient import os client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('fetch_cat/naver-map-places-scraper').call(run_input={ 'queries': ['카페'], 'location': '서울', 'maxResultsPerQuery': 10, 'includeDetails': True, 'proxyConfiguration': {'useApifyProxy': False}, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### API usage with cURL ```bash curl -X POST "https://api.apify.com/v2/acts/fetch_cat~naver-map-places-scraper/runs?token=$APIFY_TOKEN" \ -H 'Content-Type: application/json' \ -d '{ "queries": ["카페"], "location": "서울", "maxResultsPerQuery": 10, "includeDetails": true, "proxyConfiguration": { "useApifyProxy": false } }' ``` After the run finishes, fetch the default dataset from the run detail response. ### MCP usage Use Apify MCP to call this actor from Claude tools. Claude Code setup: ```bash claude mcp add apify --url "https://mcp.apify.com/?tools=fetch_cat/naver-map-places-scraper" ``` Claude Desktop JSON example: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com/?tools=fetch_cat/naver-map-places-scraper" } } } ``` Example prompts: - Find 25 cafes near Seoul City Hall and return names, phones, websites, and review counts. - Compare Naver Map restaurants in Gangnam and Hongdae for local SEO outreach. - Build a lead list of dental clinics in Busan with phone numbers and Naver URLs. ### Scheduling workflows You can schedule this actor in Apify for recurring local monitoring. Useful schedules include: - Weekly restaurant competitor checks by district - Monthly agency prospecting refreshes - Daily monitoring for a small set of client keywords - Quarterly market scans before expansion planning Keep scheduled runs focused so they stay affordable and easy to review. ### Quality checklist before scaling Before running larger batches, check a small output sample. Confirm that: - Names and categories look relevant - Addresses match the intended city or district - Naver URLs open the expected listings - Phone and website fields are present where you need them - Duplicate queries are not producing unnecessary overlap - Result limits match your budget ### Legality and responsible use This actor extracts public business listing information. You are responsible for using the data lawfully and respectfully. Do not use results for spam, harassment, unlawful profiling, or prohibited targeting. Respect applicable laws, Naver terms, privacy obligations, and recipients' communication preferences. ### Troubleshooting No results? - Try a Korean keyword. - Add a clearer location. - Lower the result limit and test a simpler query. Anti-bot challenge? - Reduce run size. - Enable Apify Proxy. - Retry with more focused Korean search terms. Missing website or phone? - Some Naver Map listings do not publish those fields. - Use `naverUrl` to inspect the listing manually when a field is critical. Unexpected location? - Add a district or neighborhood to the `location` field. - Put the location directly in the query, such as `강남 카페`. ### FAQ Can it scrape reviews? The actor returns review counts and related result metadata. It does not return full review text in the current version. Can it scrape all of Korea at once? Use multiple targeted queries by city, district, or category. One broad query is usually less useful than several focused searches. Does it require login? No. The actor is designed for public Naver Map search results. Why are some fields null? Naver Map listings do not all expose the same fields in search results. Null means the field was not available for that result. Can I use English search terms? Yes, but Korean terms are recommended for broader local coverage. ### Related scrapers Use this actor with other `fetch_cat` Apify actors for broader business-data workflows. Related workflow ideas: - Combine map data with search-result monitoring. - Enrich local leads with website or contact checks. - Compare Naver Map coverage against other public local directories. - Schedule multiple local scrapers and merge exports in a warehouse. ### Support If a run does not return the data you expected, include the input JSON, run ID, and a short description of the target location or category when requesting help. Small reproducible examples are the fastest way to diagnose query, location, or anti-bot issues. # Actor input Schema ## `queries` (type: `array`): Naver Map search terms such as 카페, restaurants in Seoul, hospitals, hotels, salons, or a brand/category name. ## `location` (type: `string`): Optional city, district, or neighborhood appended to each query. Example: Seoul, Busan, Gangnam, Hongdae. ## `maxResultsPerQuery` (type: `integer`): Maximum number of Naver Map places to save for each query. The current browser search returns up to 70 visible places per query. ## `includeDetails` (type: `boolean`): Reserved for future deeper detail-page enrichment. The current version already extracts public fields present in search results. ## `proxyConfiguration` (type: `object`): Optional Apify Proxy settings. Start without proxy; enable Apify Proxy if Naver returns an anti-bot challenge from your environment. ## Actor input object example ```json { "queries": [ "카페", "강남 맛집" ], "location": "서울", "maxResultsPerQuery": 10, "includeDetails": true, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "카페", "강남 맛집" ], "location": "서울" }; // Run the Actor and wait for it to finish const run = await client.actor("fetch_cat/naver-map-places-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": [ "카페", "강남 맛집", ], "location": "서울", } # Run the Actor and wait for it to finish run = client.actor("fetch_cat/naver-map-places-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "카페", "강남 맛집" ], "location": "서울" }' | apify call fetch_cat/naver-map-places-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetch_cat/naver-map-places-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Naver Map Places Scraper", "description": "Extract public Naver Map business listings with addresses, phones, websites, coordinates, categories, review counts, and place URLs.", "version": "0.1", "x-build-id": "ji9XyBcgsmK3RBAUZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetch_cat~naver-map-places-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetch_cat-naver-map-places-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fetch_cat~naver-map-places-scraper/runs": { "post": { "operationId": "runs-sync-fetch_cat-naver-map-places-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fetch_cat~naver-map-places-scraper/run-sync": { "post": { "operationId": "run-sync-fetch_cat-naver-map-places-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "queries" ], "properties": { "queries": { "title": "Search queries", "minItems": 1, "type": "array", "description": "Naver Map search terms such as 카페, restaurants in Seoul, hospitals, hotels, salons, or a brand/category name.", "items": { "type": "string" } }, "location": { "title": "Location hint", "type": "string", "description": "Optional city, district, or neighborhood appended to each query. Example: Seoul, Busan, Gangnam, Hongdae." }, "maxResultsPerQuery": { "title": "Maximum places per query", "minimum": 1, "maximum": 70, "type": "integer", "description": "Maximum number of Naver Map places to save for each query. The current browser search returns up to 70 visible places per query.", "default": 10 }, "includeDetails": { "title": "Include detail fields", "type": "boolean", "description": "Reserved for future deeper detail-page enrichment. The current version already extracts public fields present in search results.", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify Proxy settings. Start without proxy; enable Apify Proxy if Naver returns an anti-bot challenge from your environment.", "default": { "useApifyProxy": false } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```