Text Analyzer

#!/usr/bin/env python3 """ Text Analyzer MCP Server AI 에이전트에서 답변 문자열의 글자 수를 체크하는 FastMCP 서버 """ from fastmcp import FastMCP from typing import Dict, Any import re import unicodedata # MCP 서버 인스턴스 생성 mcp = FastMCP("Text Analyzer Server") @mcp.tool() def count_characters(text: str, include_spaces: bool = True) -> Dict[str, Any]: """ 텍스트의 글자 수를 계산합니다. Args: text: 분석할 텍스트 include_spaces: 공백을 포함할지 여부 (기본값: True) Returns: Dict containing character count analysis """ if not text: return { "total_characters": 0, "characters_without_spaces": 0, "spaces_count": 0, "text_length": 0 } total_chars = len(text) chars_without_spaces = len(text.replace(" ", "")) spaces_count = text.count(" ") result = { "total_characters": total_chars, "characters_without_spaces": chars_without_spaces, "spaces_count": spaces_count, "text_length": total_chars, "include_spaces_setting": include_spaces, "final_count": total_chars if include_spaces else chars_without_spaces } return result @mcp.tool() def count_words(text: str) -> Dict[str, Any]: """ 텍스트의 단어 수를 계산합니다. Args: text: 분석할 텍스트 Returns: Dict containing word count analysis """ if not text: return { "word_count": 0, "unique_words": 0, "average_word_length": 0.0 } # 단어 분리 (공백, 구두점 기준) words = re.findall(r'\b\w+\b', text.lower()) unique_words = set(words) avg_length = sum(len(word) for word in words) / len(words) if words else 0 return { "word_count": len(words), "unique_words": len(unique_words), "average_word_length": round(avg_length, 2) } @mcp.tool() def analyze_character_types(text: str) -> Dict[str, Any]: """ 텍스트의 문자 타입별 분석을 수행합니다. Args: text: 분석할 텍스트 Returns: Dict containing character type analysis """ if not text: return { "alphabetic": 0, "numeric": 0, "spaces": 0, "punctuation": 0, "korean": 0, "english": 0, "special_characters": 0 } counts = { "alphabetic": 0, "numeric": 0, "spaces": 0, "punctuation": 0, "korean": 0, "english": 0, "special_characters": 0 } for char in text: if char.isspace(): counts["spaces"] += 1 elif char.isalpha(): counts["alphabetic"] += 1 # 한글 문자 체크 if '\uac00' <= char <= '\ud7af': counts["korean"] += 1 elif char.isascii(): counts["english"] += 1 elif char.isnumeric(): counts["numeric"] += 1 elif unicodedata.category(char).startswith('P'): counts["punctuation"] += 1 else: counts["special_characters"] += 1 return counts @mcp.tool() def get_text_statistics(text: str) -> Dict[str, Any]: """ 텍스트의 종합적인 통계 정보를 제공합니다. Args: text: 분석할 텍스트 Returns: Dict containing comprehensive text statistics """ char_stats = count_characters(text) word_stats = count_words(text) type_stats = analyze_character_types(text) # 줄 수 계산 lines = text.split('\n') line_count = len(lines) non_empty_lines = len([line for line in lines if line.strip()]) # 문장 수 계산 (간단한 방식) sentences = re.split(r'[.!?]+', text) sentence_count = len([s for s in sentences if s.strip()]) return { "character_analysis": char_stats, "word_analysis": word_stats, "character_types": type_stats, "line_count": line_count, "non_empty_lines": non_empty_lines, "sentence_count": sentence_count, "text_preview": text[:100] + "..." if len(text) > 100 else text } @mcp.tool() def check_text_length_limit(text: str, max_length: int = 1000) -> Dict[str, Any]: """ 텍스트가 지정된 길이 제한을 초과하는지 확인합니다. Args: text: 검사할 텍스트 max_length: 최대 허용 길이 (기본값: 1000) Returns: Dict containing length check results """ current_length = len(text) is_within_limit = current_length <= max_length excess_chars = max(0, current_length - max_length) remaining_chars = max(0, max_length - current_length) return { "current_length": current_length, "max_length": max_length, "within_limit": is_within_limit, "excess_characters": excess_chars, "remaining_characters": remaining_chars, "percentage_used": round((current_length / max_length) * 100, 2) if max_length > 0 else 0 } # 리소스 정의 @mcp.resource("file://help") def get_help() -> str: """ 텍스트 분석기 사용법 도움말을 제공합니다. """ return """ Text Analyzer MCP Server 도움말 사용 가능한 도구: 1. count_characters(text, include_spaces) - 글자 수 계산 2. count_words(text) - 단어 수 계산 3. analyze_character_types(text) - 문자 타입별 분석 4. get_text_statistics(text) - 종합 통계 정보 5. check_text_length_limit(text, max_length) - 길이 제한 검사 예시: - count_characters("안녕하세요 Hello!", True) - get_text_statistics("분석할 텍스트를 입력하세요.") - check_text_length_limit("텍스트", 100) """ if __name__ == "__main__": # 서버 실행 mcp.run()