MCP 서버 구현은 벡터 검색을 통해 검색 및 처리 문서에 대한 도구를 제공, AI 조수가 관련 문서 컨텍스트와 그들의 응답을 증언 할 수 있도록.

내용 표

• 특징
• 빠른 시작
• Docker Compose 설정
• 웹 인터페이스
• 구성
• Cline 구성
• Claude 데스크탑 구성
• Acknowledgments의 특징
• 문제 해결

특징

도구

1. **search documentation **

• 벡터 검색을 사용하여 문서 검색
• 소스 정보와 관련된 펑크를 반환합니다.

2. **list sources **

• 모든 문서 소스 목록
• 각 소스에 대한 메타데이터 제공

3. **extract urls **

• 텍스트에서 URL을 추출하고 문서에 이미 있는지 확인
• 중복 문서 예방

4. **remove documentation **

• 특정 소스에서 문서를 제거
• 정리 또는 관련 문서

5. **list queue **

• 가공 큐의 모든 항목 목록
• 문서 처리의 상태 표시

6. **run queue **

• queue에서 모든 항목을 처리
• 자동으로 벡터 저장소에 새 문서를 추가

7. 명세.

RAG Documentation MCP Server

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

Table of Contents

• Features
• Quick Start
• Docker Compose Setup
• Web Interface
• Configuration
  • Cline Configuration
  • Claude Desktop Configuration
• Acknowledgments
• Troubleshooting

Features

Tools

1. search_documentation

   • Search through the documentation using vector search
   • Returns relevant chunks of documentation with source information

2. list_sources

   • List all available documentation sources
   • Provides metadata about each source

3. extract_urls

   • Extract URLs from text and check if they’re already in the documentation
   • Useful for preventing duplicate documentation

4. remove_documentation

   • Remove documentation from a specific source
   • Cleans up outdated or irrelevant documentation

5. list_queue

   • List all items in the processing queue
   • Shows status of pending documentation processing

6. run_queue

   • Process all items in the queue
   • Automatically adds new documentation to the vector store

7. clear_queue

   • Clear all items from the processing queue
   • Useful for resetting the system

8. add_documentation

   • Add new documentation directly to the system by providing a URL
   • Automatically fetches, processes, and indexes the content
   • Supports various web page formats and extracts relevant content
   • Chunks content intelligently for optimal retrieval
   • Required parameter: url (must include protocol, e.g., https://)

9. add_repository

   • Index a local code repository for documentation
   • Configure include/exclude patterns for files and directories
   • Supports different chunking strategies based on file types
   • Uses asynchronous processing to avoid MCP timeouts with large repositories
   • Provides detailed progress logging (heartbeat) to stderr during indexing
   • Required parameter: path (absolute path to repository)

10. list_repositories

    • List all indexed repositories with their configurations
    • Shows include/exclude patterns and watch status

11. update_repository

    • Re-index a repository with updated configuration
    • Can modify include/exclude patterns and other settings
    • Provides detailed progress logging (heartbeat) to stderr during re-indexing
    • Required parameter: name (repository name)

12. remove_repository

    • Remove a repository from the index
    • Deletes all associated documents from the vector database