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Tech-curator

Korean Patent MCP

by Tech-curator

kipris_get_citing_patents

Retrieve patents that cite a specific Korean patent by entering its application number. Use this tool to analyze citation networks and identify subsequent innovations building upon prior art.

Instructions

특정 특허를 인용한 후행 특허들을 조회합니다.

Args:
    application_number: 기준 특허의 출원번호 (필수)
    response_format: 응답 형식 ('markdown' 또는 'json')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
application_numberYes
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main MCP tool handler function decorated with @mcp.tool. It handles input parameters, initializes the API client, calls the core get_citing_patents method, and formats the response as markdown or JSON.
    @mcp.tool(name="kipris_get_citing_patents")
    async def kipris_get_citing_patents(
        application_number: str,
        response_format: str = "markdown"
    ) -> str:
        """특정 특허를 인용한 후행 특허들을 조회합니다.
        
        Args:
            application_number: 기준 특허의 출원번호 (필수)
            response_format: 응답 형식 ('markdown' 또는 'json')
        """
        # Get API key from session config or environment
        api_key = get_config_value("kiprisApiKey") or os.getenv("KIPRIS_API_KEY", "")
        if api_key:
            init_client_with_key(api_key)
        
        client = get_kipris_client()
        if client is None:
            return f"❌ 오류: {get_init_error() or 'API 클라이언트 초기화 실패'}"
        
        app_num = application_number.replace("-", "")
        
        try:
            result = await client.get_citing_patents(app_num)
            
            if response_format == "json":
                return json.dumps({
                    "base_application_number": app_num,
                    "citing_count": len(result),
                    "citing_patents": result
                }, ensure_ascii=False, indent=2)
            return format_citing_patents_markdown(result, app_num)
        except Exception as e:
            return f"❌ 조회 오류: {str(e)}"
  • Core helper method in KiprisAPIClient that performs the actual HTTP request to the KIPRIS 'citingInfo' endpoint, parses the XML response, and extracts the list of citing patents.
    async def get_citing_patents(
        self,
        application_number: str
    ) -> List[Dict[str, Any]]:
        """
        특정 특허를 인용한 후행 특허 조회
        
        Args:
            application_number: 기준 특허의 출원번호
            
        Returns:
            인용 특허 목록
        """
        params = {
            "standardCitationApplicationNumber": application_number
        }
        
        root = await self._make_request(
            self.ENDPOINTS["citing_info"],
            params
        )
        
        if root is None:
            return []
        
        citing_patents = []
        for item in root.findall(".//citingInfo"):
            citing_info = {
                "citing_application_number": self._get_text(item, "ApplicationNumber"),
                "standard_citation_number": self._get_text(item, "StandardCitationApplicationNumber"),
                "status_code": self._get_text(item, "StandardStatusCode"),
                "status_name": self._get_text(item, "StandardStatusCodeName"),
                "citation_type_code": self._get_text(item, "CitationLiteratureTypeCode"),
                "citation_type_name": self._get_text(item, "CitationLiteratureTypeCodeName"),
            }
            citing_patents.append(citing_info)
        
        return citing_patents
  • Helper function used by the handler to format the list of citing patents into a readable markdown string.
    def format_citing_patents_markdown(citations: list, base_app_num: str) -> str:
        lines = []
        lines.append("## 인용 특허 조회 결과")
        lines.append("")
        lines.append(f"기준 특허 `{base_app_num}`를 인용한 후행 특허: **{len(citations)}**건")
        lines.append("")
        
        if not citations:
            lines.append("이 특허를 인용한 후행 특허가 없습니다.")
            return "\n".join(lines)
        
        for i, cite in enumerate(citations, 1):
            lines.append("---")
            lines.append(f"**[{i}]** 출원번호: `{cite.get('citing_application_number', '-')}`")
            lines.append(f"- 상태: {cite.get('status_name', '-')} ({cite.get('status_code', '-')})")
            lines.append(f"- 인용유형: {cite.get('citation_type_name', '-')}")
            lines.append("")
        
        return "\n".join(lines)
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 of behavioral disclosure. It states the tool retrieves data (조회), implying a read-only operation, but does not address permissions, rate limits, error handling, or response behavior beyond the response_format parameter. For a tool with no annotations, this leaves significant gaps in understanding its operational traits.

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 and well-structured: a clear purpose statement followed by an 'Args' section listing parameters with brief explanations. It avoids redundancy and is front-loaded with the main function. However, the 'Args' section could be integrated more smoothly into the narrative.

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 should cover return values), the description's focus on purpose and parameters is adequate. However, with no annotations and low schema coverage, it lacks details on behavioral aspects like error cases or performance. It meets minimum viability but has clear gaps in context for safe and effective use.

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?

The description adds some semantic context: it explains that application_number is for the '기준 특허' (base patent) and is required, and response_format specifies the output format with options. However, schema description coverage is 0%, so parameters are undocumented in the schema. The description compensates partially by clarifying meanings but does not fully detail constraints or examples, such as the format of application_number.

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: '특정 특허를 인용한 후행 특허들을 조회합니다' (Retrieve patents that cite a specific patent). It specifies the verb (조회/retrieve) and resource (후행 특허들/citing patents), and distinguishes from siblings like kipris_get_patent_detail (which gets details) and kipris_search_patents (which searches). However, it doesn't explicitly contrast with siblings beyond the inherent difference in function.

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 does not mention sibling tools or other contexts, nor does it specify prerequisites or exclusions. The usage is implied by the purpose but lacks explicit 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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