Mcp-build-memory-tracker-server

Ramneek82810/Mcp-build-memory-tracker-server

3.2

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The MCP Build Memory Tracker Server is a robust memory tracking server designed to enhance AI applications by managing contextual memory across sessions using the MCP framework.

🧠 MCP Build Memory Tracker Server

A powerful memory tracking server built using the MCP (Multi-Service Conversational Platform) framework. This project monitors, stores, and manages contextual memory from MCP-powered AI applications, enabling smarter and more coherent interactions across sessions.

🚀 Features

  • 📦 Tracks memory across multiple user sessions
  • 🧩 Integrates seamlessly with MCP client/server setups
  • 🗃️ Uses efficient in-memory and persistent memory stores
  • 🔄 Supports real-time memory updates and deletions
  • ✅ Minimal setup with uvicorn for local development

📁 Project Structure

Mcp-build-memory-tracker-server/
│
├── memory/                 # Core memory logic and backend
│   ├── memory_store.py     # In-memory and persistent memory handler
│   └── utils.py            # Helper utilities
│
├── server.py              # Main MCP memory tracker server
└── README.md              # You're reading it!

⚙️ Installation

1. Clone the Repository

git clone https://github.com/Ramneek82810/Mcp-build-memory-tracker-server.git
cd Mcp-build-memory-tracker-server

2. Create and Activate Virtual Environment (optional but recommended)

python -m venv .venv
source .venv/bin/activate    # On Windows use: .venv\Scripts\activate

3. Install Dependencies

pip install fastapi uvicorn mcp

🧪 Run the Server Locally

uvicorn server:app --reload

Or if using uv (recommended for MCP projects):

uv run server.py

The server will be available at http://localhost:8000

🧠 How Memory Works

  • Stores contextual data like conversation history, instructions, and metadata
  • Each memory is scoped by:
    • session_id
    • tool_name
    • key
  • Supports:
    • GET /memory
    • POST /memory
    • DELETE /memory

🔌 Integration with MCP

This server is designed to work with MCP's memory protocol.

Example MCP Tool Client Usage:

from mcp import ClientSession
# Your logic to call memory endpoints

Make sure to configure your client to point to this server when running in development mode.

📌 Todo

  • Add persistent storage backend (Redis/SQLite)
  • Secure memory endpoints
  • Add Swagger UI for API testing
  • Write unit tests

🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first.