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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

MCP server providing access to US patent data (2000-2024) via Rememberizer's knowledge retrieval tools, enabling semantic search and document management for patent information.

README.md

Rememberizer MCP Server for Common Knowledge

<!-- CK_DESCRIPTION_START --> This Common Knowledge contains US patent data sourced from the Google Patents Public Datasets. The dataset includes bibliographic information and full-text data for US patents spanning from January 1, 2000 through November 2024, provided by IFI CLAIMS Patent Services. <!-- CK_DESCRIPTION_END -->

Please note that rememberizer-mcp-us-patent-ck 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): 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
  1. 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
  1. 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
  1. 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
  1. 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
  1. 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-us-patent-ck.

!MseeP AI Helper

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

"mcpServers": {
  "rememberizer": {
      "command": "uvx",
      "args": ["rememberizer-mcp-us-patent-ck"]
    }
}

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:

  • _What is this Common Knowledge?_
  • _List all documents that it has 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.

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