[{"_1":2,"_339":-5,"_340":-5},"loaderData",{"_3":4,"_22":23,"_235":236},"root",{"_5":6,"_7":8},"toasts",[],"visitor",{"_9":10,"_11":12},"viewportWidth",1280,"visitorSession",{"_13":14,"_16":17,"_18":-5,"_19":20,"_21":-5},"attributes",[15],"bot","id",18046839,"membership","referenceId","0199d013-274b-71c7-9a22-d23226418aee","userAccount","routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_24":25,"_26":-5,"_27":28,"_29":40,"_152":153,"_233":234},"availableLocales",[],"githubUser","locale",{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","A simple AI development tool that helps users interact with AI through natural language commands, offering 29 tools across thinking, memory, browser, code quality, planning, and time management capabilities.","name","Hi-AI","readme","# Hi-AI: 자연어 기반 AI 개발 도구\n\n[![npm version](https://badge.fury.io/js/@su-record%2Fhi-ai.svg)](https://www.npmjs.com/package/@su-record/hi-ai)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![MCP Compatible](https://img.shields.io/badge/MCP-Compatible-blue.svg)](https://modelcontextprotocol.io)\n\nModel Context Protocol (MCP) 기반의 자연어 처리 개발 도구로, AI와의 원활한 협업을 통해 개발 생산성을 극대화합니다.\n\n## 📊 프로젝트 개요\n\nHi-AI는 Anthropic의 MCP(Model Context Protocol) 표준을 구현한 서버로, 개발자가 자연스러운 대화를 통해 복잡한 개발 작업을 수행할 수 있도록 설계되었습니다. 🎯 33개의 특화된 도구를 제공하며, 키워드 기반 의도 인식을 통해 명시적인 명령어 없이도 적절한 도구를 자동으로 실행합니다. ✨\n\n## 🎯 핵심 기능\n\n### 1. 🗣️ 자연어 처리 기반 도구 실행\n- **🔍 키워드 기반 의도 인식**: 사용자의 자연스러운 발화에서 키워드를 추출하여 적절한 도구 자동 실행\n- **🌍 다국어 지원**: 한국어와 영어 키워드 동시 지원으로 글로벌 사용성 확보\n- **🧠 컨텍스트 인식**: 대화 맥락을 고려한 지능형 도구 선택\n\n### 2. 💾 메모리 관리 시스템\n- **⚡ 자동 컨텍스트 저장**: 토큰 한계 접근 시 중요 정보 자동 보존\n- **🔄 세션 기반 복원**: 이전 작업 상태를 완벽하게 재현\n- **📊 우선순위 기반 메모리 관리**: 중요도에 따른 선택적 정보 보존\n\n### 3. 🔍 시맨틱 코드 분석 (v1.1.0 신규)\n- **🎯 심볼 검색**: 프로젝트 전체에서 함수, 클래스, 변수 등 정확한 심볼 위치 파악\n- **📍 참조 찾기**: 특정 심볼이 사용되는 모든 위치를 정확하게 추적\n- **🧩 AST 기반 분석**: ts-morph를 활용한 정확한 코드 구조 이해\n- **📝 다언어 지원**: TypeScript, JavaScript, JSX, TSX 파일 분석 가능\n\n### 4. 📏 코드 품질 분석\n- **📈 복잡도 메트릭스**: Cyclomatic, Cognitive, Halstead 복잡도 분석\n- **🧩 AST 기반 분석 추가**: analyze_complexity · check_coupling_cohesion · break_down_problem 개선\n - JavaScript 프로젝트도 `allowJs: true` 옵션으로 ts-morph 파싱 지원\n- **🔗 결합도/응집도 평가**: 모듈 구조의 건전성 검증\n- **💡 실시간 개선 제안**: 코드 품질 향상을 위한 구체적 방안 제시\n\n### 5. 🎯 프롬프트 엔지니어링\n- **✨ 자동 프롬프트 강화**: 모호한 요청을 구체적이고 실행 가능한 형태로 변환\n- **📊 품질 평가 시스템**: 프롬프트의 명확성, 구체성, 맥락성 점수화\n\n## 🔧 기술 사양\n\n### 시스템 아키텍처\n\n

\n $\"시스템$ \n

\n\n### 도구 카테고리 및 구성\n6\n| 카테고리 | 도구 수 | 주요 기능 |\n|----------|---------|-----------|\n| 🔍 시맨틱 분석 | 2개 | 심볼 검색, 참조 찾기 (v1.1.0 신규) |\n| 🧠 사고 도구 | 6개 | 문제 분석, 단계별 분해, 사고 체인 생성 |\n| 💾 메모리 도구 | 10개 | 컨텍스트 저장/복원, 세션 관리, 우선순위 설정 |\n| 🌐 브라우저 도구 | 2개 | 콘솔 로그 모니터링, 네트워크 요청 분석 |\n| 📏 코드 품질 도구 | 6개 | 복잡도 분석, 품질 검증, 개선 제안 |\n| 📋 계획 도구 | 4개 | PRD 생성, 사용자 스토리, 로드맵 작성 |\n| 🎯 프롬프트 도구 | 2개 | 프롬프트 강화, 품질 분석 |\n| 🕐 시간 도구 | 1개 | 타임존 기반 시간 조회 |\n\n## 📦 설치 및 구성\n\n### 🖥️ 시스템 요구사항\n- Node.js 18.0 이상 ⚙️\n- TypeScript 5.0 이상 📘\n- MCP 호환 에디터 (Claude Desktop, Cursor, Windsurf) 🛠️\n\n### 🚀 설치 방법\n\n#### 옵션 1: Smithery 플랫폼 (권장) ⭐\n```bash\n# 원클릭 설치\nhttps://smithery.ai/server/@su-record/hi-ai\n```\n\n#### 옵션 2: NPM 패키지 📦\n```bash\n# 글로벌 설치\nnpm install -g @su-record/hi-ai\n\n# 로컬 설치\nnpm install @su-record/hi-ai\n```\n\n### ⚙️ MCP 구성\n\n```json\n{\n \"mcpServers\": {\n \"hi-ai\": {\n \"command\": \"hi-ai\",\n \"args\": [],\n \"env\": {}\n }\n }\n}\n```\n\n## 🔑 키워드 매핑 시스템\n\n### 자동 도구 실행 매커니즘\n\nHi-AI는 사용자 입력에서 특정 키워드를 감지하여 관련 도구를 자동으로 실행합니다. 이는 각 도구의 `description` 필드에 정의된 키워드 패턴을 통해 구현됩니다.\n\n#### 메모리 관리 키워드 매핑\n\n| 도구 | 한국어 키워드 | 영어 키워드 | 기능 |\n|------|--------------|------------|------|\n| `save_memory` | 기억해, 저장해 | remember, save this, memorize | 정보를 장기 메모리에 저장 |\n| `recall_memory` | 떠올려, 기억나 | recall, remind me, what was | 저장된 정보 검색 |\n| `auto_save_context` | 커밋, 저장 | commit, checkpoint, backup | 현재 컨텍스트 자동 저장 |\n| `list_memories` | 뭐 있었지, 목록 | list memories, show saved | 저장된 메모리 목록 조회 |\n\n#### 코드 분석 키워드 매핑\n\n| 도구 | 한국어 키워드 | 영어 키워드 | 기능 |\n|------|--------------|------------|------|\n| `analyze_complexity` | 복잡도, 복잡한지 | complexity, how complex | 코드 복잡도 메트릭 분석 |\n| `validate_code_quality` | 품질, 리뷰, 검사 | quality, review, validate | 코드 품질 종합 평가 |\n| `suggest_improvements` | 개선, 리팩토링 | improve, refactor, optimize | 개선 방안 제시 |\n\n### 키워드 인식 알고리즘\n\n```typescript\n// 도구 정의 예시\nexport const enhancePromptDefinition: ToolDefinition = {\n name: 'enhance_prompt',\n description: 'IMPORTANT: This tool should be automatically called when requests are vague, \n too short (under 20 chars), or when users say \"구체적으로\", \"자세히\", \n \"명확하게\", \"be specific\", \"more detail\", \"clarify\"...',\n inputSchema: { /* ... */ }\n};\n```\n\n## 💼 엔터프라이즈 기능\n\n### 1. 🔧 확장성\n- **📦 모듈형 아키텍처**: 각 도구가 독립적으로 동작하여 선택적 활성화 가능\n- **🔌 플러그인 시스템**: 커스텀 도구 추가를 위한 표준화된 인터페이스\n\n### 2. 🔒 보안 및 프라이버시\n- **🏠 로컬 실행**: 모든 처리가 로컬에서 수행되어 데이터 유출 방지\n- **🔐 메모리 격리**: 세션별 독립적인 메모리 공간 할당\n\n### 3. ⚡ 성능 최적화\n- **🚀 경량 설계**: 최소한의 의존성으로 빠른 실행 속도 보장\n- **🔄 비동기 처리**: 모든 도구가 비동기로 동작하여 블로킹 방지\n\n## 📈 사용 통계 및 메트릭\n\n### 📊 도구별 활용도 분석\n- 💾 메모리 도구: 평균 호출 빈도 최상위 (35%)\n- 📏 코드 품질 도구: 코드 리뷰 시 집중 사용 (25%)\n- 🎯 프롬프트 도구: 초기 요구사항 정의 시 활용 (20%)\n\n### ⚡ 성능 지표\n- ⏱️ 평균 응답 시간: < 100ms\n- 💻 메모리 사용량: < 50MB\n- 🔄 동시 처리 가능 세션: 무제한\n\n## 🔬 기술적 구현 세부사항\n\n### 📘 TypeScript 타입 시스템\n```typescript\ninterface ToolResult {\n content: Array<{\n type: 'text';\n text: string;\n }>;\n}\n\ninterface ToolDefinition {\n name: string;\n description: string;\n inputSchema: {\n type: 'object';\n properties: Record;\n required: string[];\n };\n}\n```\n\n### 🔌 MCP 프로토콜 구현\n- ✅ 표준 준수: MCP 1.0 스펙 완벽 구현\n- 🛡️ 에러 처리: 체계적인 에러 코드 및 복구 메커니즘\n- 📡 스트리밍 지원: 대용량 결과의 점진적 전송\n\n## 🤝 기여 가이드\n\n### 🛠️ 개발 환경 설정\n```bash\ngit clone https://github.com/su-record/hi-ai.git\ncd hi-ai\nnpm install\nnpm run dev\n```\n\n### 📝 코드 스타일\n- ✨ ESLint + Prettier 설정 준수\n- 📚 모든 퍼블릭 API에 JSDoc 주석 필수\n- 🧪 단위 테스트 커버리지 80% 이상 유지\n\n### 🔄 Pull Request 프로세스\n1. 🌿 기능 브랜치 생성: `feature/tool-name`\n2. 💬 변경사항 커밋: Conventional Commits 형식 준수\n3. ✅ 테스트 통과 확인\n4. 🎯 PR 생성 및 리뷰 요청\n\n## 📜 라이선스\n\nMIT License - 자유롭게 사용, 수정, 배포 가능\n\n## 🏆 인용 및 참조\n\n이 프로젝트를 연구나 상업적 용도로 사용하실 경우, 다음과 같이 인용해 주시기 바랍니다:\n\n```bibtex\n@software{hi-ai2024,\n author = {Su},\n title = {Hi-AI: Natural Language MCP Server for AI-Assisted Development},\n year = {2024},\n url = {https://github.com/su-record/hi-ai}\n}\n```\n\n---\n\n

\nHi-AI - AI 기반 개발의 새로운 패러다임 🚀
\nMade with ❤️ by Su × Claude\n

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