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jikime

Naver Search MCP Server

search_doc

Search for academic papers and reports using keywords with page navigation for comprehensive research results.

Instructions

Searches for academic papers, reports, etc. 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

  • The handler function implementing the core logic of the 'search_doc' tool. It handles pagination, prepares API parameters, and invokes the shared _make_api_call to retrieve and format results from the Naver 'doc.json' endpoint.
    async def search_doc(query: str, display: int = 10, page: int = 1) -> str:
        """
        Searches for academic papers, reports, etc. 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("doc.json", params, DocResult, "Academic Papers")
  • server.py:549-552 (registration)
    The @mcp.tool decorator registering the 'search_doc' tool, specifying its name and description for the MCP protocol.
    @mcp.tool(
      name="search_doc",
      description="Searches for academic papers, reports, etc. using the given keyword. The page parameter allows for page navigation."
    )
  • Pydantic model (DocResult) used for schema validation of the API response data specific to document/academic papers search, which is parsed and formatted in the handler.
    class DocResult(SearchResultBase): items: List[DocItem]
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'page navigation' for pagination, which adds some behavioral context, but fails to disclose critical traits like whether this is a read-only operation, rate limits, authentication needs, or what the search returns (though an output schema exists). For a search tool with zero annotation coverage, this is inadequate.

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?

The description is concise with two sentences that are front-loaded: the first states the core purpose, and the second adds pagination context. There is no wasted text, but it could be slightly more structured by explicitly listing parameters or usage scenarios.

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's moderate complexity (3 parameters, no annotations, but with an output schema), the description is minimally complete. It covers the basic purpose and pagination, but lacks details on search scope, result format, or error handling. The presence of an output schema mitigates the need to explain return values, but more context on behavior and parameters is needed for full adequacy.

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 schema provides no parameter descriptions. The description adds minimal semantics: it explains that 'page parameter allows for page navigation,' giving context for the 'page' parameter. However, it does not cover 'query' or 'display' parameters, leaving two of three parameters without semantic explanation. This partial compensation results in a baseline score.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Searches for academic papers, reports, etc. using the given keyword.' It specifies the verb ('searches'), resource ('academic papers, reports, etc.'), and scope ('using the given keyword'). However, it does not explicitly differentiate from sibling tools like search_blog or search_book, which lowers it from a 5.

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. It mentions 'page navigation' for pagination but does not specify contexts, exclusions, or comparisons to sibling tools such as search_blog or search_news, leaving the agent with no usage direction.

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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