What can you do with this server?

The **Naver Search MCP Server** enables integration with Naver Search API and DataLab API for comprehensive searches and trend analysis across Naver services. **Capabilities:** * Search across Naver's web documents, news, blogs, cafes, shopping, images, KnowledgeiN, books, encyclopedia, academic papers, and local places * Analyze search term trends and shopping trends by various demographics (device, gender, age) * Analyze shopping category trends and keyword performance **Technical Features:** * Customizable parameters for search result control (sorting, position, display count) * Compatible with AI clients like Claude Desktop, Cursor, Windsurf, and Cline * Supports Docker deployment * Requires Naver Developers API keys for authentication

Which integrations are available for this server?

Optional containerization platform for deploying the MCP server in an isolated environment. Enables comprehensive search across various [Naver](/mcp/servers/integrations/naver) services (web, news, blogs, shopping, images, KnowledgeiN, books, encyclopedia, academic papers, local places) and data trend analysis through Naver Search API and DataLab API. Required runtime environment for the MCP server, version 18 or higher needed for server operation. Required package manager, version 8 or higher needed for dependency management.

Naver Search MCP Server

MCP server for Naver Search API and DataLab API integration, enabling comprehensive search across various Naver services and data trend analysis.

Version History

1.0.45 (2025-09-28)

Resolved Smithery compatibility issues so you can use the latest features through Smithery
Replaced the Excel export in category search with JSON for better compatibility
Restored the search_webkr tool for Korean web search
Fully compatible with Smithery platform installation

1.0.44 (2025-08-31)

Added the get_current_korean_time tool for essential Korea Standard Time context
Referenced the time tool across existing tool descriptions for temporal queries
Improved handling of "today", "now", and "current" searches with temporal context
Expanded Korean date and time formatting outputs with multiple formats

1.0.40 (2025-08-21)

Added the find_category tool with fuzzy matching so you no longer need to check category numbers manually in URLs
Enhanced parameter validation with Zod schema
Improved the category search workflow
Implemented a level-based category ranking system that prioritizes top-level categories

1.0.30 (2025-08-04)

MCP SDK upgraded to 1.17.1
Fixed compatibility issues with Smithery specification changes
Added comprehensive DataLab shopping category code documentation

1.0.2 (2025-04-26)

README updated: cafe article search tool and version history section improved

1.0.1 (2025-04-26)

Cafe article search feature added
Shopping category info added to zod
Source code refactored

1.0.0 (2025-04-08)

Initial release

Prerequisites

Naver Developers API Key (Client ID and Secret)
Node.js 18 or higher
NPM 8 or higher
Docker (optional, for container deployment)

Getting API Keys

Visit Naver Developers
Click "Register Application"
Enter application name and select ALL of the following APIs:
- Search (for blog, news, book search, etc.)
- DataLab (Search Trends)
- DataLab (Shopping Insight)
Set the obtained Client ID and Client Secret as environment variables

Tool Details

Available tools:

🕐 Time & Context Tools

get_current_korean_time: Fetch the current Korea Standard Time (KST) along with comprehensive date and time details. Use this whenever a search or analysis requires temporal context such as "today", "now", or "current" in Korea.

🆕 Category Search

find_category: Category search tool so you no longer need to manually check category numbers in URLs for trend and shopping insight searches. Just describe the category in natural language.

Search Tools

search_webkr: Search Naver web documents
search_news: Search Naver news
search_blog: Search Naver blogs
search_cafearticle: Search Naver cafe articles
search_shop: Search Naver shopping
search_image: Search Naver images
search_kin: Search Naver KnowledgeiN
search_book: Search Naver books
search_encyc: Search Naver encyclopedia
search_academic: Search Naver academic papers
search_local: Search Naver local places

DataLab Tools

datalab_search: Analyze search term trends
datalab_shopping_category: Analyze shopping category trends
datalab_shopping_by_device: Analyze shopping trends by device
datalab_shopping_by_gender: Analyze shopping trends by gender
datalab_shopping_by_age: Analyze shopping trends by age group
datalab_shopping_keywords: Analyze shopping keyword trends
datalab_shopping_keyword_by_device: Analyze shopping keyword trends by device
datalab_shopping_keyword_by_gender: Analyze shopping keyword trends by gender
datalab_shopping_keyword_by_age: Analyze shopping keyword trends by age group

For a complete list of category codes, you can download from Naver Shopping Partner Center or extract them by browsing Naver Shopping categories.

🎯 Business Use Cases & Scenarios

🛍️ E-commerce Market Research

// Fashion trend discovery find_category("fashion") → Check top fashion categories and codes datalab_shopping_category → Analyze seasonal fashion trends datalab_shopping_age → Identify fashion target demographics datalab_shopping_keywords → Compare "dress" vs "jacket" vs "coat"

📱 Digital Marketing Strategy

// Beauty industry analysis find_category("cosmetics") → Find beauty categories datalab_shopping_gender → 95% female vs 5% male shoppers datalab_shopping_device → Mobile dominance in beauty shopping datalab_shopping_keywords → "tint" vs "lipstick" keyword performance

🏢 Business Intelligence & Competitive Analysis

// Tech product insights find_category("smartphone") → Check electronics categories datalab_shopping_category → Track iPhone vs Galaxy trends datalab_shopping_age → 20-30s as main smartphone buyers datalab_shopping_device → PC vs mobile shopping behavior

📊 Seasonal Business Planning

// Holiday shopping analysis find_category("gift") → Gift categories datalab_shopping_category → Black Friday, Christmas trends datalab_shopping_keywords → "Mother's Day gift" vs "birthday gift" datalab_shopping_age → Age-based gift purchasing patterns

🎯 Customer Persona Development

// Fitness market analysis find_category("exercise") → Sports/fitness categories datalab_shopping_gender → Male vs female fitness spending datalab_shopping_age → Primary fitness demographics (20-40s) datalab_shopping_keywords → "home workout" vs "gym" trend analysis

📈 Advanced Analysis Scenarios

Market Entry Strategy

Category Discovery: Use find_category to explore market segments
Trend Analysis: Identify growing vs declining categories
Demographic Targeting: Age/gender analysis for customer targeting
Competitive Intelligence: Keyword performance comparison
Device Strategy: Mobile vs PC shopping optimization

Product Launch Planning

Market Validation: Category growth trends and seasonality
Target Customers: Demographic analysis for product positioning
Marketing Channels: Device preferences for advertising strategy
Competitive Landscape: Keyword competition and opportunities
Pricing Strategy: Category performance and price correlation

Performance Monitoring

Category Health: Monitor product category trends
Keyword Tracking: Track brand and product keyword performance
Demographic Shifts: Monitor changing customer demographics
Seasonal Patterns: Plan inventory and marketing campaigns
Competitive Benchmarking: Compare performance against category averages

Quick Reference: Popular Category Codes

Category	Code	Korean
Fashion/Clothing	50000000	패션의류
Cosmetics/Beauty	50000002	화장품/미용
Digital/Electronics	50000003	디지털/가전
Sports/Leisure	50000004	스포츠/레저
Food/Beverages	50000008	식품/음료
Health/Medical	50000009	건강/의료용품

💡 Tip: Use find_category with fuzzy searches like "beauty", "fashion", "electronics" to easily find categories.

Related MCP server: Naver MCP Server

Installation

Method 1: NPX Installation (Recommended)

The most reliable way to use this MCP server is through NPX. For detailed package information, see the NPM package page.

Claude Desktop Configuration

Add to Claude Desktop config file (%APPDATA%\Claude\claude_desktop_config.json on Windows, ~/Library/Application Support/Claude/claude_desktop_config.json on macOS/Linux):

{ "mcpServers": { "naver-search": { "command": "npx", "args": ["-y", "@isnow890/naver-search-mcp"], "env": { "NAVER_CLIENT_ID": "your_client_id", "NAVER_CLIENT_SECRET": "your_client_secret" } } } }

Cursor AI Configuration

Add to mcp.json:

{ "mcpServers": { "naver-search": { "command": "npx", "args": ["-y", "@isnow890/naver-search-mcp"], "env": { "NAVER_CLIENT_ID": "your_client_id", "NAVER_CLIENT_SECRET": "your_client_secret" } } } }

Method 2: Smithery Installation (Alternative - Known Issues)

⚠️ Important Notice: Smithery installations can run into connection timeouts and freezes because of issues in the Smithery WebSocket relay infrastructure. This is a known platform limitation rather than a bug in this MCP server. For stable usage, we strongly recommend sticking with Method 1 (NPX installation).

Known issues on Smithery:

Server initialization may hang or time out
Error -32001: Request timed out can appear
WebSocket connections can drop immediately after the handshake
The server can exit unexpectedly before processing requests

If you still want to try Smithery:

For Claude Desktop:

npx -y @smithery/cli@latest install @isnow890/naver-search-mcp --client claude

For other AI clients:

# Cursor npx -y @smithery/cli@latest install @isnow890/naver-search-mcp --client cursor # Windsurf npx -y @smithery/cli@latest install @isnow890/naver-search-mcp --client windsurf # Cline npx -y @smithery/cli@latest install @isnow890/naver-search-mcp --client cline

If you encounter timeouts on Smithery, switch back to Method 1 (NPX) for a stable experience.

Method 3: Local Installation

For local development or custom modifications:

Step 1: Download and Build Source Code

Clone with Git

git clone https://github.com/isnow890/naver-search-mcp.git cd naver-search-mcp npm install npm run build

Or Download ZIP File

Download the latest version from GitHub Releases
Extract the ZIP file to your desired location
Navigate to the extracted folder in terminal:

cd /path/to/naver-search-mcp npm install npm run build

⚠️ Important: You must run npm run build after installation to generate the dist folder that contains the compiled JavaScript files.

Step 2: Claude Desktop Configuration

After building, you'll need the following information:

NAVER_CLIENT_ID: Client ID from Naver Developers
NAVER_CLIENT_SECRET: Client Secret from Naver Developers
Installation Path: Absolute path to the downloaded folder

Windows Configuration

Add to Claude Desktop config file (%APPDATA%\Claude\claude_desktop_config.json):

{ "mcpServers": { "naver-search": { "type": "stdio", "command": "cmd", "args": [ "/c", "node", "C:\\path\\to\\naver-search-mcp\\dist\\src\\index.js" ], "cwd": "C:\\path\\to\\naver-search-mcp", "env": { "NAVER_CLIENT_ID": "your-naver-client-id", "NAVER_CLIENT_SECRET": "your-naver-client-secret" } } } }

macOS/Linux Configuration

Add to Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json):

{ "mcpServers": { "naver-search": { "type": "stdio", "command": "node", "args": ["/path/to/naver-search-mcp/dist/src/index.js"], "cwd": "/path/to/naver-search-mcp", "env": { "NAVER_CLIENT_ID": "your-naver-client-id", "NAVER_CLIENT_SECRET": "your-naver-client-secret" } } } }

Path Configuration Important Notes

⚠️ Important: You must change the following paths in the above configuration to your actual installation paths:

Windows: Change C:\\path\\to\\naver-search-mcp to your actual downloaded folder path
macOS/Linux: Change /path/to/naver-search-mcp to your actual downloaded folder path
Build Path: Make sure the path points to dist/src/index.js (not just index.js)

Finding your path:

# Check current location pwd # Absolute path examples # Windows: C:\Users\username\Downloads\naver-search-mcp # macOS: /Users/username/Downloads/naver-search-mcp # Linux: /home/username/Downloads/naver-search-mcp

Step 3: Restart Claude Desktop

After completing the configuration, completely close and restart Claude Desktop to activate the Naver Search MCP server.

Alternative Installation Methods

Method 4: Docker Installation

For containerized deployment:

docker run -i --rm \ -e NAVER_CLIENT_ID=your_client_id \ -e NAVER_CLIENT_SECRET=your_client_secret \ mcp/naver-search

Docker configuration for Claude Desktop:

{ "mcpServers": { "naver-search": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "NAVER_CLIENT_ID=your_client_id", "-e", "NAVER_CLIENT_SECRET=your_client_secret", "mcp/naver-search" ] } } }

Build

Docker build:

docker build -t mcp/naver-search .

License

MIT License