Rememberizer AI

What is mcp-server-rememberizer?

mcp-server-rememberizer is a Model Context Protocol (MCP) server designed to interact with Rememberizer.ai, a document and knowledge management API. It enables Large Language Models (LLMs) to seamlessly search, retrieve, and manage documents and integrations within the Rememberizer ecosystem.

How to use mcp-server-rememberizer?

mcp-server-rememberizer can be installed and used in several ways:

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: Search for "Rememberizer" and install the server.

Configuration:

Environment Variable: Set REMEMBERIZER_API_TOKEN with your API token from Rememberizer.ai.
Claude Desktop: Add the server configuration to claude_desktop_config.json.
SkyDeck AI Helper App: Configure the REMEMBERIZER_API_TOKEN within the app.

Once configured, you can interact with the server through your LLM (e.g., Claude Desktop, SkyDeck AI GenStudio) by asking questions like "What is my Rememberizer account?" or "List all documents that I have there."

Key Features of mcp-server-rememberizer

Resource Access: Provides access to Documents and Slack discussions.
Tools for Knowledge Management:
- retrieve_semantically_similar_internal_knowledge: Retrieves semantically similar text chunks from your Rememberizer knowledge base.
- smart_search_internal_knowledge: Performs agentic searches across various sources like Slack, Gmail, Dropbox, Google Drive, and uploaded files.
- list_internal_knowledge_systems: Lists available integrations and sources of internal knowledge.
- rememberizer_account_information: Retrieves your Rememberizer.ai account details.
- list_personal_team_knowledge_documents: Provides a paginated list of all documents in your knowledge system.
- remember_this: Saves text information into your Rememberizer.ai knowledge system for future retrieval.

Use Cases of mcp-server-rememberizer

Enhanced LLM Capabilities: Empower LLMs with the ability to access and manage personal and team knowledge.
Intelligent Information Retrieval: Quickly find relevant information from diverse sources using semantic search and smart queries.
Automated Knowledge Management: Programmatically save and organize information within Rememberizer.ai.
Context-Aware Interactions: Provide LLMs with the necessary context from your knowledge base for more accurate and relevant responses.

FAQ from mcp-server-rememberizer

Q: What kind of resources can I access through this server? A: The server provides access to Documents and Slack discussions from your Rememberizer.ai knowledge system.

Q: How can I filter search results by date? A: The retrieve_semantically_similar_internal_knowledge and smart_search_internal_knowledge tools allow you to specify from_datetime_ISO8601 and to_datetime_ISO8601 parameters to filter results by date.

Q: Can I save new information using this server? A: Yes, the remember_this tool allows you to save text information into your Rememberizer.ai knowledge system.

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

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
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
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 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.

SkyDeck 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 SkyDeck AI Helper App

Add the env REMEMBERIZER_API_TOKEN to mcp-server-rememberizer.

SkyDeck 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...

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Rememberizer AI Overview