Rememberizer의 문서 및 지식 관리 API와 상호 작용하는 모델 Context Protocol 서버. 이 서버는 큰 언어 모델을 검색, 검색, 검색, 관리, 문서 및 통합을 통해 Rememberizer.

mcp-server-rememberizer]는 현재 개발 중이며, 기능은 변경될 수 있습니다.

부품

자원

서버는 두 가지 유형의 리소스에 대한 액세스를 제공합니다 : 문서 또는 슬랙 토론

도구

1. retrieve_semantically_similar_internal_knowledge

• 연결된 Rememberizer Personal/team 내부 지식 및 메모리 저장소에서 텍스트 및 검색 cosine 유사한 일치의 블록을 보내십시오.
• 입력:
• match_this (string): 지식의 세균성 유사한 펑크를 찾으려면 400 단어 문장까지
• n_results (integer, 옵션): semantically 유사한 펑크의 텍스트를 반환합니다. 더 많은 정보를 위해 'n results=3’를 최대 5, 'n results=10’로 사용하십시오.
• from_datetime_ISO8601 (문자, 선택 사항) : 시간대 (예 : 2023-01-01T00:00:00Z)와 ISO 8601 형식의 시작 날짜. 특정 날짜에서 필터 결과에 사용

MCP Server Rememberizer

A Model Context Protocol server for interacting with Rememberizer’s document and knowledge management API. This server enables Large Language Models to search, retrieve, and manage documents and integrations through Rememberizer.

Please note that mcp-server-rememberizer is currently in development and the functionality may be subject to change.

Components

Resources

The server provides access to two types of resources: Documents or Slack discussions

Tools

1. retrieve_semantically_similar_internal_knowledge

   • Send a block of text and retrieve cosine similar matches from your connected Rememberizer personal/team internal knowledge and memory repository
   • Input:
     • match_this (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
     • n_results (integer, optional): Number of semantically similar chunks of text to return. Use ‘n_results=3’ for up to 5, and ‘n_results=10’ for more information
     • from_datetime_ISO8601 (string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific date
     • to_datetime_ISO8601 (string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific date
   • Returns: Search results as text output

2. smart_search_internal_knowledge

   • Search for documents in Rememberizer in its personal/team internal knowledge and memory repository using a simple query that returns the results of an agentic search. The search may include sources such as Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
   • Input:
     • query (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
     • user_context (string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared results
     • n_results (integer, optional): Number of semantically similar chunks of text to return. Use ‘n_results=3’ for up to 5, and ‘n_results=10’ for more information
     • from_datetime_ISO8601 (string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific date
     • to_datetime_ISO8601 (string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific date
   • Returns: Search results as text output