# naver_search

> Use this tool when you need to search for information on the web, as it provides a simple interface to query the Naver search engine and retrieve relevant results. It solves problems such as finding specific data, news, or websites, and can be used in various contexts like research, data collection, or fact-checking. The tool takes a search query as input and returns a list of relevant search results as output.

Canonical page: https://skillsregistry.net/skills/parkkyeonghoon-naver-search  
JSON: https://api.skillsregistry.net/v1/skills/parkkyeonghoon-naver-search

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** search
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/parkkyeonghoon/naver_search)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "parkkyeonghoon-naver-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/parkkyeonghoon-naver-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/parkkyeonghoon-naver-search/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt