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2025-04-02

Vector Memory MCP Server - An MCP server with vector-based memory storage capabilities

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Aleph-10: Vector Memory MCP Server

Aleph-10 is a Model Context Protocol (MCP) server that combines weather data services with vector-based memory storage. This project provides tools for retrieving weather information and managing semantic memory through vector embeddings.

Features

  • Weather Information: Get weather alerts and forecasts using the National Weather Service API
  • Vector Memory: Store and retrieve information using semantic search
  • Multiple Embedding Options: Support for both cloud-based (Google Gemini) and local (Ollama) embedding providers
  • Metadata Support: Add and filter by metadata for efficient memory management

Getting Started

Prerequisites

  • Node.js 18.x or higher
  • pnpm package manager

Installation

  1. Clone the repository
git clone https://github.com/yourusername/aleph-10.git
cd aleph-10
  1. Install dependencies
pnpm install
  1. Configure environment variables (create a .env file in the project root)
EMBEDDING_PROVIDER=gemini
GEMINI_API_KEY=your_gemini_api_key
VECTOR_DB_PATH=./data/vector_db
LOG_LEVEL=info
  1. Build the project
pnpm build
  1. Run the server
node build/index.js

Usage

The server implements the Model Context Protocol and provides the following tools:

Weather Tools

  • get-alerts: Get weather alerts for a specific US state

    • Parameters: state (two-letter state code)
  • get-forecast: Get weather forecast for a location

    • Parameters: latitude and longitude

Memory Tools

  • memory-store: Store information in the vector database

    • Parameters: text (content to store), metadata (optional associated data)
  • memory-retrieve: Find semantically similar information

    • Parameters: query (search text), limit (max results), filters (metadata filters)
  • memory-update: Update existing memory entries

    • Parameters: id (memory ID), text (new content), metadata (updated metadata)
  • memory-delete: Remove entries from the database

    • Parameters: id (memory ID to delete)
  • memory-stats: Get statistics about the memory store

    • Parameters: none

Configuration

The following environment variables can be configured:

Variable Description Default
EMBEDDING_PROVIDER Provider for vector embeddings (gemini or ollama) gemini
GEMINI_API_KEY API key for Google Gemini -
OLLAMA_BASE_URL Base URL for Ollama API http://localhost:11434
VECTOR_DB_PATH Storage location for vector database ./data/vector_db
LOG_LEVEL Logging verbosity info

Development

Project Structure

The project follows a modular structure:

aleph-10/
├── src/                         # Source code
│   ├── index.ts                 # Main application entry point
│   ├── weather/                 # Weather service module
│   ├── memory/                  # Memory management module
│   ├── utils/                   # Shared utilities
│   └── types/                   # TypeScript type definitions
├── tests/                       # Test files
└── vitest.config.ts             # Vitest configuration

Running Tests

The project uses Vitest for testing. Run tests with:

# Run tests once
pnpm test

# Run tests in watch mode during development
pnpm test:watch

# Run tests with UI (optional)
pnpm test:ui

Building

pnpm build

License

This project is licensed under the ISC License.

Acknowledgments

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    Reviews

    3 (1)
    Avatar
    user_bPxALz6H
    2025-04-16

    As a loyal user of MCP applications, I highly recommend Aleph-10 by bjkemp. This tool is incredibly efficient and user-friendly, significantly streamlining my workflow. The comprehensive documentation available on GitHub ensures a smooth start and helps you unlock the full potential of Aleph-10 effortlessly. Whether you're a newbie or a pro, this application is a game-changer in the MCP space. Check it out at https://github.com/bjkemp/aleph-10.