Rememberizer MCP Server

$uvx rememberizer-mcp-asdasd
README.md

Enables interaction with Rememberizer.ai knowledge repositories

Rememberizer MCP Server for Common Knowledge

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Please note that rememberizer-mcp-asdasd 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 SkyDeck AI Helper App

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

SkyDeck AI Helper

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

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

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...

Tools (6)

retrieve_semantically_similar_internal_knowledgeRetrieve cosine similar matches from connected personal/team internal knowledge and memory repository.
smart_search_internal_knowledgeSearch for documents using a simple query that returns results of an agentic search across multiple sources.
list_internal_knowledge_systemsList the sources of personal/team internal knowledge such as Slack, Gmail, and Dropbox.
rememberizer_account_informationGet information about your Rememberizer.ai account including holder name and email address.
list_personal_team_knowledge_documentsRetrieves a paginated list of all documents in your personal/team knowledge system.
remember_thisSave a piece of text information in your Rememberizer.ai knowledge system for future recall.

Configuration

claude_desktop_config.json
{
  "mcpServers": {
    "rememberizer": {
      "command": "uvx",
      "args": ["rememberizer-mcp-asdasd"]
    }
  }
}

Try it

What is this Common Knowledge?
List all documents that it has there.
Give me a quick summary about the project proposal in my Google Drive.
Search my Slack discussions for any mention of the Q4 roadmap.
Remember this: The client prefers blue for the logo design.

Frequently Asked Questions

What are the key features of Rememberizer MCP Server?

Semantic search using cosine similarity across connected knowledge repositories.. Agentic search across multiple sources including Slack, Gmail, Dropbox, and Google Drive.. Ability to save and 'remember' new text information for future recall.. Paginated document listing and source integration management..

What can I use Rememberizer MCP Server for?

Retrieving specific project details buried in Slack or Gmail conversations.. Summarizing internal team documents stored across different cloud drives.. Building a persistent memory for AI agents by storing new facts via the 'remember_this' tool.. Auditing connected knowledge systems and listing available internal documents..

How do I install Rememberizer MCP Server?

Install Rememberizer MCP Server by running: uvx rememberizer-mcp-asdasd

What MCP clients work with Rememberizer MCP Server?

Rememberizer MCP Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Use Rememberizer MCP Server with Conare

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