What is Rememberizer

The MCP Server Rememberizer is a server designed to facilitate interaction between Large Language Models and Rememberizer’s document and knowledge management API. It allows users to search, retrieve, and manage documents as well as internal knowledge through various tools integrated into the platform.

Use cases

This server can be used for retrieving semantically similar internal knowledge, conducting smart searches across a range of document sources, and managing personal or team knowledge systems. Typical use cases include finding relevant information quickly, organizing documentation, and enhancing knowledge retrieval processes within teams.

How to use

To utilize the MCP Server Rememberizer, users must install it through methods such as mcp-get.com or Smithery CLI. Post-installation, it requires configuration via environment variables, specifically the Rememberizer API token. Users can then interact with the server’s tools by sending queries or documents for processing.

Key features

Key features of the MCP Server Rememberizer include the ability to retrieve semantically similar chunks of knowledge, perform smart searches across various document sources like Slack, Gmail, and Google Drive, list available internal knowledge systems, and save information for future retrieval. Additionally, it provides user account information and a paginated listing of documents.

Where to use

The MCP Server Rememberizer can be implemented within applications that support model context protocols, such as Claude Desktop or the SkyDeck AI Helper app. It is particularly useful in environments that require efficient knowledge management and retrieval across diverse document systems.

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

3. 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

4. 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

5. 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

6. 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 mcp-get.com

npx @michaellatman/mcp-get@latest install mcp-server-rememberizer

Via Smithery

npx -y @smithery/cli install mcp-server-rememberizer --client claude

Via SkyDeck AI Helper App

If you have SkyDeck AI Helper app installed, you can search for “Rememberizer” and install the mcp-server-rememberizer.

Configuration

Environment Variables

The following environment variables are required:

• REMEMBERIZER_API_TOKEN: Your Rememberizer API token

You can register an API key by creating your own Common Knowledge in Rememberizer.

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Usage with SkyDeck AI Helper App

Add the env REMEMBERIZER_API_TOKEN to mcp-server-rememberizer.

With support from the Rememberizer MCP server, you can now ask the following questions in your Claude Desktop app or SkyDeck AI GenStudio

• What is my Rememberizer account?

• List all documents that I have 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.