Which integrations are available for this server?

Enables semantic search and retrieval of information from Dropbox documents stored in the Rememberizer knowledge repository, with support for date filtering and smart search capabilities. Allows semantic search and retrieval of information from Gmail messages stored in the Rememberizer knowledge repository, with contextual search and date-based filtering. Provides access to Google Drive documents through semantic search and retrieval tools, allowing queries across personal and team knowledge stored in the Rememberizer system. Enables searching and retrieving information from Slack discussions stored in Rememberizer, with support for semantic similarity matching and smart agentic search across conversation history.

How do I use Rememberizer MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Rememberizer MCP Server find our Q4 marketing strategy from last year's Slack discussions" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Rememberizer MCP Server for Common Knowledge

A private CK for testing MCP server from QuangH.

Please note that rememberizer-mcp-quanghs-gdrive 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): A query of up to 400 words 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
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): A query of up to 400 words 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-aware 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
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 future
  - content (string): The information you wish to memorize
- Returns: Confirmation data

Installation

Via MseeP AI Helper App

If you have the MseeP AI Helper app installed, you can search for "Rememberizer" and install the rememberizer-mcp-quanghs-gdrive.

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

"mcpServers": { "rememberizer": { "command": "uvx", "args": ["rememberizer-mcp-quanghs-gdrive"] } }

Usage with MseeP 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: