Provides access to Dropbox documents as a source of internal knowledge, making them searchable through semantic queries
Enables searching and retrieving information from Gmail as part of the internal knowledge repository
Integrates with Google Drive documents, allowing them to be searched and retrieved as part of the internal knowledge repository
Allows access to Slack discussions as a source of internal knowledge and memory, making them searchable and retrievable through semantic queries
Rememberizer MCP Server for Common Knowledge
Common Knowledge: mcp的知识
Please note that rememberizer-mcp-mcp
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
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 knowledgen_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 informationfrom_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 dateto_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
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 knowledgeuser_context
(string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared resultsn_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 informationfrom_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 dateto_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
list_internal_knowledge_systems
- List the sources of personal/team internal knowledge. These may include Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input: None required
- Returns: List of available integrations
rememberizer_account_information
- Get information about your Rememberizer.ai personal/team knowledge repository account. This includes account holder name and email address
- Input: None required
- Returns: Account information details
list_personal_team_knowledge_documents
- Retrieves a paginated list of all documents in your personal/team knowledge system. Sources could include Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input:
page
(integer, optional): Page number for pagination, starts at 1 (default: 1)page_size
(integer, optional): Number of documents per page, range 1-1000 (default: 100)
- Returns: List of documents
remember_this
- Save a piece of text information in your Rememberizer.ai knowledge system so that it may be recalled in future through tools retrieve_semantically_similar_internal_knowledge or smart_search_internal_knowledge
- Input:
name
(string): Name of the information. This is used to identify the information in the futurecontent
(string): The information you wish to memorize
- Returns: Confirmation data
Installation
Via SkyDeck AI Helper App
If you have SkyDeck AI Helper app installed, you can search for "Rememberizer" and install the rememberizer-mcp-mcp.
Configuration
Usage with Claude Desktop
Add this to your claude_desktop_config.json
:
Usage with SkyDeck AI Helper App
With support from the Rememberizer MCP server for Common Knowledge, you can now ask the following questions in your Claude Desktop app or SkyDeck AI GenStudio
- What is this Common Knowledge?
- List all documents that it has there.
- Give me a quick summary about "..."
- and so on...
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
This server cannot be installed
Enables accessing and managing personal/team internal knowledge repository with tools for semantic search, smart search, document listing, and saving information for future recall.
Related MCP Servers
- AsecurityAlicenseAqualityProvides tools for listing and retrieving content from different knowledge bases using semantic search capabilities.Last updated -2020TypeScriptThe Unlicense
- AsecurityFlicenseAqualityProvides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.Last updated -68TypeScript
- -securityAlicense-qualityA powerful knowledge management system that forges wisdom from experiences, insights, and best practices. Built with Qdrant vector database for efficient knowledge storage and retrieval.Last updated -4TypeScriptMIT License
- -securityFlicense-qualityIntelligent knowledge base management tool that enables searching, browsing, and analyzing documents across multiple datasets with smart document analysis capabilities.Last updated -14Python