mcp_batch_process

Process multiple texts simultaneously to detect, anonymize, encrypt, or decrypt personally identifiable information using GPT-4o-based detection and cryptographic methods.

Instructions

MCP Tool: 여러 텍스트 일괄 처리

Args:
    texts (List[str]): 처리할 텍스트 리스트
    
Returns:
    Dict[str, Any]: 일괄 처리 결과

Input Schema

TableJSON Schema

Name	Required	Description	Default
`texts`	Yes

Implementation Reference

mcp_pii_tools.py:556-569 (handler)

The main handler function for the 'mcp_batch_process' MCP tool. It is decorated with @mcp.tool() for automatic registration and delegates to MCPPIIProcessor.batch_process for the core logic.

@mcp.tool()
def mcp_batch_process(texts: List[str]) -> Dict[str, Any]:
    """
    MCP Tool: 여러 텍스트 일괄 처리
    
    Args:
        texts (List[str]): 처리할 텍스트 리스트
        
    Returns:
        Dict[str, Any]: 일괄 처리 결과
    """
    processor = MCPPIIProcessor()
    return processor.batch_process(texts)

mcp_pii_tools.py:480-525 (helper)

Core helper method in MCPPIIProcessor class that implements the batch PII processing logic by iterating over texts and calling process_text on each.

def batch_process(self, texts: List[str]) -> Dict[str, Any]:
    """
    여러 텍스트를 일괄 처리 (MCP Tool용)
    
    Args:
        texts (List[str]): 처리할 텍스트 리스트
        
    Returns:
        Dict[str, Any]: MCP Tool 응답 형식
    """
    try:
        start_time = time.time()
        results = []
        
        for i, text in enumerate(texts):
            result = self.process_text(text)
            result["index"] = i
            results.append(result)
        
        processing_time = time.time() - start_time
        
        # 전체 통계
        total_pii = sum(result["count"] for result in results if result["success"])
        successful_count = sum(1 for result in results if result["success"])
        
        return {
            "success": True,
            "results": results,
            "total_texts": len(texts),
            "successful_count": successful_count,
            "total_pii_detected": total_pii,
            "processing_time": processing_time,
            "average_time_per_text": processing_time / len(texts) if texts else 0
        }
        
    except Exception as e:
        return {
            "success": False,
            "error": str(e),
            "results": [],
            "total_texts": len(texts),
            "successful_count": 0,
            "total_pii_detected": 0,
            "processing_time": 0,
            "average_time_per_text": 0
        }

mcp_pii_tools.py:869-882 (schema)

JSON schema definition for the batch_process tool input parameters, specifying 'texts' as a required array of strings.

"batch_process": {
    "name": "batch_process",
    "description": "여러 텍스트를 일괄적으로 PII(개인 정보) 처리합니다.",
    "parameters": {
        "type": "object",
        "properties": {
            "texts": {
                "type": "array",
                "items": {"type": "string"},
                "description": "처리할 텍스트 리스트"
            }
        },
        "required": ["texts"]
    }

mcp_pii_tools.py:556-569 (registration)

The @mcp.tool() decorator registers the function as an MCP tool named 'mcp_batch_process'.

@mcp.tool()
def mcp_batch_process(texts: List[str]) -> Dict[str, Any]:
    """
    MCP Tool: 여러 텍스트 일괄 처리
    
    Args:
        texts (List[str]): 처리할 텍스트 리스트
        
    Returns:
        Dict[str, Any]: 일괄 처리 결과
    """
    processor = MCPPIIProcessor()
    return processor.batch_process(texts)

MCP PII Tools