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Rememberizer Us Patent Ck

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

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About

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

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.

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
  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): 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
  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 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.

from github.com/skydeckai/rememberizer-mcp-us-patent-ck

Installing Rememberizer Us Patent Ck

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/skydeckai/rememberizer-mcp-us-patent-ck

FAQ

Is Rememberizer Us Patent Ck MCP free?

Yes, Rememberizer Us Patent Ck MCP is free — one-click install via Unyly at no cost.

Does Rememberizer Us Patent Ck need an API key?

No, Rememberizer Us Patent Ck runs without API keys or environment variables.

Is Rememberizer Us Patent Ck hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Rememberizer Us Patent Ck in Claude Desktop, Claude Code or Cursor?

Open Rememberizer Us Patent Ck on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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