Naver Search MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NAVER_CLIENT_ID | Yes | Your Naver Client ID | |
| NAVER_CLIENT_SECRET | Yes | Your Naver Client Secret |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
| prompts | {} |
| resources | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_webkrC | Perform a search on Naver Web Documents. (네이버 웹문서 검색) |
| search_newsC | Perform a search on Naver News. (네이버 뉴스 검색) |
| search_blogC | Perform a search on Naver Blog. (네이버 블로그 검색) |
| search_shopC | Perform a search on Naver Shopping. (네이버 쇼핑 검색) |
| search_imageC | Perform a search on Naver Image. (네이버 이미지 검색) |
| search_kinA | Perform a search on Naver KnowledgeiN. (네이버 지식iN 검색) |
| search_bookC | Perform a search on Naver Book. (네이버 책 검색) |
| search_encycB | Perform a search on Naver Encyclopedia. (네이버 지식백과 검색) |
| search_academicB | Perform a search on Naver Academic. (네이버 전문자료 검색) |
| search_localC | Perform a search on Naver Local. (네이버 지역 검색) |
| search_cafearticleB | Perform a search on Naver Cafe Articles. (네이버 카페글 검색) |
| datalab_searchC | Perform a trend analysis on Naver search keywords. (네이버 검색어 트렌드 분석) |
| datalab_shopping_categoryB | Perform a trend analysis on Naver Shopping category. (네이버 쇼핑 카테고리별 트렌드 분석) |
| datalab_shopping_by_deviceB | Perform a trend analysis on Naver Shopping by device. (네이버 쇼핑 기기별 트렌드 분석) |
| datalab_shopping_by_genderB | Perform a trend analysis on Naver Shopping by gender. (네이버 쇼핑 성별 트렌드 분석) |
| datalab_shopping_by_ageC | Perform a trend analysis on Naver Shopping by age. (네이버 쇼핑 연령별 트렌드 분석) |
| datalab_shopping_keywordsB | Perform a trend analysis on Naver Shopping keywords. (네이버 쇼핑 키워드별 트렌드 분석) |
| datalab_shopping_keyword_by_deviceC | Perform a trend analysis on Naver Shopping keywords by device. (네이버 쇼핑 키워드 기기별 트렌드 분석) |
| datalab_shopping_keyword_by_genderB | Perform a trend analysis on Naver Shopping keywords by gender. (네이버 쇼핑 키워드 성별 트렌드 분석) |
| datalab_shopping_keyword_by_ageB | Perform a trend analysis on Naver Shopping keywords by age. (네이버 쇼핑 키워드 연령별 트렌드 분석) |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 20 tools
Each search_* tool targets a distinct Naver content type (news, blog, shop, etc.), and each datalab_* tool covers a specific trend analysis dimension. The descriptions clearly differentiate otherwise similar-looking datalab_shopping variants.
All tool names follow a consistent snake_case pattern with a clear prefix (search_ or datalab_) followed by the target or dimension. This uniformity makes the tool set easy to predict and navigate.
With 20 tools, the set is on the heavier side. While each tool maps to a distinct Naver API endpoint, the datalab_shopping family alone accounts for 7 tools, making the overall surface feel somewhat large for the server's scope.
The server covers the major Naver search categories and trend analysis dimensions, providing a robust set for most query needs. Minor gaps exist, such as missing some specialized search categories (e.g., movie, people), but these are not critical.