What is Mcp Rememberizer Vectordb

mcp-rememberizer-vectordb is a Model Context Protocol server designed for large language models (LLMs) to interact with the Rememberizer Vector Store, facilitating semantic document retrieval.

Use cases

Use cases include building intelligent chatbots that can retrieve relevant information, enhancing search functionalities in applications, and managing large sets of documents for research or customer support.

How to use

To use mcp-rememberizer-vectordb, you can utilize various tools such as rememberizer_vectordb_search for semantic searches, rememberizer_vectordb_agentic_search for enhanced searches with LLM Agents, and rememberizer_vectordb_create_document to add new documents to your Vector Store.

Key features

Key features include semantic similarity search, LLM Agents augmentation for improved search results, paginated document retrieval, and the ability to create and manage documents within the Vector Store.

Where to use

mcp-rememberizer-vectordb can be used in fields such as artificial intelligence, natural language processing, knowledge management, and any application requiring efficient document retrieval based on semantic understanding.

Rememberizer Vector Store MCP Server

A Model Context Protocol server for LLMs to interact with Rememberizer Vector Store.

Components

Resources

The server provides access to your Vector Store’s documents in Rememberizer.

Tools

1. rememberizer_vectordb_search

   • Search for documents in your Vector Store by semantic similarity
   • Input:
     • q (string): Up to a 400-word sentence to find semantically similar chunks of knowledge
     • n (integer, optional): Number of similar documents to return (default: 5)

2. rememberizer_vectordb_agentic_search

   • Search for documents in your Vector Store by semantic similarity with LLM Agents augmentation
   • Input:
     • query (string): Up to a 400-word sentence to find semantically similar chunks of knowledge. This query can be augmented by our LLM Agents for better results.
     • n_chunks (integer, optional): Number of similar documents to return (default: 5)
     • 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 (default: None)

3. rememberizer_vectordb_list_documents

   • Retrieves a paginated list of all documents
   • 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

4. rememberizer_vectordb_information

   • Get information of your Vector Store
   • Input: None required
   • Returns: Vector Store information details

5. rememberizer_vectordb_create_document

   • Create a new document for your Vector Store
   • Input:
     • text (string): The content of the document
     • document_name (integer, optional): A name for the document

6. rememberizer_vectordb_delete_document

   • Delete a document from your Vector Store
   • Input:
     • document_id (integer): The ID of the document you want to delete

7. rememberizer_vectordb_modify_document

   • Change the name of your Vector Store document
   • Input:
     • document_id (integer): The ID of the document you want to modify

Installation

Via mcp-get.com: Use mcp-get command to automatically set up the Rememberizer MCP Vector Store MCP Server.

npx @michaellatman/mcp-get@latest install mcp-rememberizer-vectordb

Via SkyDeck AI Helper App: If you have SkyDeck AI Helper app installed, you can search for “Rememberizer” and install the mcp-rememberizer-vectordb.

Configuration

Environment Variables

The following environment variables are required:

• REMEMBERIZER_VECTOR_STORE_API_KEY: Your Rememberizer Vector Store API token

You can register an API key by create your own Vector Store in Rememberizer.

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Usage with SkyDeck AI Helper App

Add the env REMEMBERIZER_VECTOR_STORE_API_KEY to mcp-rememberizer-vectordb.

License

This MCP server is licensed under the Apache License 2.0. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the Apache License. For more details, please see the LICENSE file in the project repository.