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Integrate Rememberizer Knowledge with LLMs

Search your team's Rememberizer knowledge base semantically across Slack, Gmail, Drive, and Dropbox, and save new memories.

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Works with slackgmaildropboxgoogle drive
SkyDeck AI Inc
Maintainer?
91
Spark score
out of 100
Updated 3 months ago
Version release/0.1.2
Models
universal
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Why it matters

Connect your LLM to the Rememberizer knowledge management system to enable semantic search, document retrieval, and memory storage across various personal and team data sources.

Outcomes

What it gets done

01

Search and retrieve information semantically from your Rememberizer knowledge base.

02

Save and manage documents and knowledge for future recall.

03

Access account information and list available knowledge documents.

04

Integrate with data sources like Slack, Gmail, Dropbox, and Google Drive.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-rememberizer-ai | bash

Capabilities

Tools your agent gets

retrieve_semantically_similar_internal_knowledge

Retrieves semantically similar matches from your Rememberizer persona based on a text block.

smart_search_internal_knowledge

Searches documents in Rememberizer using a simple query and returns agent search results.

list_internal_knowledge_systems

Lists sources of personal/team internal knowledge including Slack, Gmail, and Dropbox.

rememberizer_account_information

Retrieves information about your Rememberizer.ai personal/team knowledge repository account.

list_personal_team_knowledge_documents

Retrieves a paginated list of all documents in your personal/team knowledge system.

remember_this

Saves text information to your Rememberizer.ai knowledge system for future retrieval.

Overview

Rememberizer AI MCP Server

Rememberizer AI MCP Server lets an AI assistant semantically search and retrieve documents from connected sources (Slack, Gmail, Dropbox, Google Drive, uploaded files) and save new information for future recall, authenticated via a Rememberizer API token. Use it for AI-assisted search across a team's centralized Rememberizer knowledge base. This server is under active development and functionality may still change.

What it does

Rememberizer AI MCP Server connects an LLM to Rememberizer's document and knowledge management platform, letting it semantically search and retrieve documents from connected sources - Slack, Gmail, Dropbox, Google Drive, and uploaded files - and save new pieces of information for future recall.

When to use - and when NOT to

Use it when you want an AI assistant to find semantically similar information across your team's connected knowledge sources, run an agentic search that pulls from multiple integrations at once, browse your document list, check account details, or explicitly memorize a new piece of text for later retrieval. Note this server is under active development and its functionality may still change.

Capabilities

  • retrieve_semantically_similar_internal_knowledge: find cosine-similarity matches for a text snippet (up to 400 words) in your knowledge repository, with n_results count (e.g. n_results=3 returns up to 5 chunks, n_results=10 returns more) and optional from_datetime_ISO8601/to_datetime_ISO8601 date filters.
  • smart_search_internal_knowledge: agentic search across Slack, Gmail, Dropbox, Google Drive, and uploaded files, with a query (up to 400 words), optional user_context (a conversation summary supplied for better context-aware results), result count, and date filters.
  • list_internal_knowledge_systems: list connected knowledge sources (Slack, Gmail, Dropbox, Google Drive, uploaded files).
  • rememberizer_account_information: get account holder name and email.
  • list_personal_team_knowledge_documents: paginated list of all documents in the knowledge system (page, page_size up to 1000).
  • remember_this: save a named piece of text information for future retrieval via the search tools, taking a name (used to identify the information later) and the content to memorize.

How to install

uvx mcp-server-rememberizer

Or install via the MseeP AI Helper app by searching for "Rememberizer". Register an API key by creating a Common Knowledge in Rememberizer, then configure Claude Desktop:

{
  "mcpServers": {
    "rememberizer": {
      "command": "uvx",
      "args": ["mcp-server-rememberizer"],
      "env": { "REMEMBERIZER_API_TOKEN": "your_rememberizer_api_token" }
    }
  }
}

REMEMBERIZER_API_TOKEN is required for all operations.

Example questions the documentation suggests once configured: "What is my Rememberizer account?", "List all documents that I have there.", and "Give me a quick summary about '...'".

The project has passed an MseeP.ai security assessment and can also be installed through the MseeP AI Helper app by searching for "Rememberizer" instead of installing manually.

Who it's for

Teams using Rememberizer to centralize knowledge from Slack, Gmail, Drive, and Dropbox who want an AI assistant to search and add to that knowledge base conversationally instead of switching between source apps.

Source README

MseeP.ai Security Assessment Badge

MCP Server Rememberizer

Verified on MseeP

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

Manual Installation

uvx mcp-server-rememberizer

Via MseeP AI Helper App

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

MseeP AI Helper

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:

"mcpServers": {
  "rememberizer": {
      "command": "uvx",
      "args": ["mcp-server-rememberizer"],
      "env": {
        "REMEMBERIZER_API_TOKEN": "your_rememberizer_api_token"
      }
    },
}

Usage with MseeP AI Helper App

Add the env REMEMBERIZER_API_TOKEN to mcp-server-rememberizer.

MseeP AI Helper Configuration

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...

To learn more about Rememberizer MCP Server: https://docs.rememberizer.ai/personal-use/integrations/rememberizer-mcp-servers

FAQ

Common questions

Discussion

Questions & comments · 0

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