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jikime

Naver Search MCP Server

search_webkr

Search for web documents using keywords with page navigation to find relevant online information through Naver Search.

Instructions

Searches for web documents using the given keyword. The page parameter allows for page navigation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
displayNo
pageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:589-592 (registration)
    MCP tool registration for 'search_webkr' using the @mcp.tool decorator.
    @mcp.tool(
      name="search_webkr",
      description="Searches for web documents using the given keyword. The page parameter allows for page navigation."
    )
  • The handler function that executes the tool logic: calculates pagination, prepares params, and delegates to shared _make_api_call with webkr-specific endpoint and model.
    async def search_webkr(query: str, display: int = 10, page: int = 1) -> str:
        """
        Searches for web documents using the given keyword. The page parameter allows for page navigation.
    
        Args:
            query (str): The keyword to search for
            display (int, optional): The number of results to display. Default is 10.
            page (int, optional): The starting page number. Default is 1.
        """
        start = calculate_start(page, display)
        display = min(display, 100)
        params = {"query": query, "display": display, "start": start}
        return await _make_api_call("webkr.json", params, WebkrResult, "Web Document")
  • Pydantic model for the overall webkr search result structure, inheriting SearchResultBase and specifying items as List[WebkrItem].
    class WebkrResult(SearchResultBase): items: List[WebkrItem]
  • Type alias defining WebkrItem as DescriptionItem, which provides title, link, and description fields.
    WebkrItem = DescriptionItem
  • Base Pydantic model for description-containing items like WebkrItem, extending BaseItem with optional description field.
    class DescriptionItem(BaseItem):
        description: Optional[str] = None
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions 'page navigation' which hints at pagination behavior, but doesn't disclose other important traits like rate limits, authentication needs, what 'web documents' includes (e.g., HTML pages, PDFs), or the search scope. For a search tool with no annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences that are reasonably efficient. The first sentence states the core purpose, and the second adds parameter context. While it could be more front-loaded with key details, there's minimal waste, and each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which reduces need to describe return values) but no annotations and 3 parameters with 0% schema coverage, the description is moderately complete. It covers the basic purpose and hints at pagination, but lacks details on search behavior, result format, or differentiation from siblings, leaving room for improvement.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds meaning for the 'page' parameter ('allows for page navigation'), but doesn't explain 'query' (beyond 'given keyword') or 'display' at all. With 3 parameters and poor schema coverage, the description provides only partial semantic context, meeting the baseline for minimal compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Searches for web documents using the given keyword' which provides a clear verb ('searches') and resource ('web documents'), but it doesn't distinguish this tool from its many siblings (e.g., search_blog, search_news, search_image) that also search different types of content. The purpose is understandable but lacks differentiation from similar tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like search_blog or search_news. It mentions page navigation but doesn't explain when this tool is appropriate compared to other search tools in the sibling list. There's no context about use cases or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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