Naver Search MCP

Use for Korean web search, Naver News, Blog, Cafe, Shopping, Image, Knowledge iN, Local search, and Naver DataLab trend analysis through the published npm MCP server.

Use this skill for Korean search tasks that are better served by Naver than general web search: news, blogs, cafe posts, shopping, images, Knowledge iN, books, encyclopedia, academic content, local places, and DataLab trend analysis.

한국 웹 검색, 네이버 뉴스/블로그/카페/쇼핑/이미지/지식iN/지역 검색, 네이버 DataLab 검색어 트렌드와 쇼핑인사이트 분석에 사용합니다.

github: https://github.com/isnow890/naver-search-mcp

This skill wraps the published MCP server:

bash

npx -y @isnow890/naver-search-mcp

Setup

• Install from ClawHub with openclaw skills install naver-search-mcp.
• Requires NAVER_CLIENT_ID and NAVER_CLIENT_SECRET from Naver Developers.
• In OpenClaw, apiKey maps to NAVER_CLIENT_SECRET because this skill declares primaryEnv: NAVER_CLIENT_SECRET.
• Provide NAVER_CLIENT_ID through the skill env config or OpenClaw environment.
• Restart OpenClaw or the Gateway after changing credentials.
• Do not ask users to clone this repository for normal use; cloning is only for development.

Example OpenClaw config:

json

{
  "skills": {
    "entries": {
      "naver-search-mcp": {
        "enabled": true,
        "apiKey": "your_naver_client_secret",
        "env": {
          "NAVER_CLIENT_ID": "your_naver_client_id"
        }
      }
    }
  }
}

Search Guidance

• Prefer this skill when the user wants Korean-source results, Naver-specific results, Korean shopping data, or Korean local data.
• Choose the tool that matches intent: news, blog reviews, cafe discussions, shopping, images, local places, academic/book/encyclopedia lookup, or general Korean web search.
• Summarize results instead of dumping raw API output. Include source, date, link, price, location, or category details when useful.

DataLab Guidance

• Use datalab_search for keyword trend comparisons.
• For shopping insight requests, call find_category first when the user gives a natural-language category such as 화장품, 노트북, or 여성의류.
• find_category is the main advantage of this MCP: users should not have to inspect Naver Shopping or DataLab URLs manually to find category codes.
• After selecting a category code, use the matching shopping trend tool for overall, device, gender, age, or keyword analysis.
• Ask the user only when multiple category candidates are genuinely ambiguous.
• For relative dates like today, recent, or current, use "today" when supported or state the assumed date range clearly.