mcp-rememberizer-vectordb 0.1.3

A Model Context Protocol server for interacting with Rememberizer Vector Store (https://docs.rememberizer.ai/developer/vector-stores).

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

Manual Installation: Use uvx command to install the Rememberizer Vector Store MCP Server.

uvx mcp-rememberizer-vectordb

Via MseeP AI Helper App: If you have MseeP AI Helper app installed, you can search for "Rememberizer VectorDb" 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:

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

Usage with MseeP 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.