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memory_plus

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License: MIT visitors

Introduction

memory plus provides a local RAG‑backed memory store for your MCP agent, so it can record, retrieve, list, and visualize "memories" (notes, ideas, context) across sessions. Think of it as a lightweight personal knowledge base that your agent consults and updates automatically.

🏆 This repo won First Place in the Infosys Cambridge AI Centre Hackathon!

Features

  • Record Memories: Persist user data, ideas, or important context for future runs.
  • Retrieve Memories: Keyword‑ or topic‑based search over past entries.
  • Recent Memories: Quickly see the last N stored items.
  • Update Memories: Update existing memories with new information.
  • Visualize Memory Graph: Interactive clusters showing how memories interrelate.

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Prerequisites

# Create & activate a virtual environment
python3 -m venv .venv  
source .venv/bin/activate  

Installation

# Install uv if you haven't already
pip install uv

# Run the memory server using uvx
uvx memory-server

Usage

The server provides several tools:

  • record: Record new memories
  • retrieve: Search for relevant memories
  • recent: Get recent memories
  • update: Update existing memories
  • visualize: Create memory visualization
  • set_whether_to_annonimize: Toggle anonymization

Configuration

Add the memory server to any MCP‑capable client by adding this to your JSON config:

{
  "servers": {
    "memory_server": {
      "type": "stdio",
      "command": "fastmcp",
      "args": ["run", "absolute/path/to/memory.py"]
    }
  }
}

🧠 One-Line Import

If you have past information—such as emails, chats, or AI conversations—that you'd like to store in the memory server, simply export them as a text file and run the following one-liner:

python load_text_to_memory.py path/to/your/previous_memory.txt

RoadMap

  • Memory Update
  • Improved prompt engineering for memory recording
  • Better Visualization of Memory Graph
  • Possible Graph Database Integration
  • Neon/Supabase Integration
  • Web UI for Memory Management

License

This project is licensed under the MIT License. See LICENSE for details.

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