# ContextMemory: MCP Server & 3D Visualizer 🧠

An ultra-lightweight, lightning-fast Model Context Protocol (MCP) Server and 3D Visualizer designed to act as a **plug-and-play package**. You can use this repository to instantly create your own custom MCP memory server for *any* project—simply by plugging in your own Neo4j Aura database credentials!

## 🌟 Features
- **Plug-and-Play MCP Server**: Instantly give your AI coding assistants (Antigravity, OpenCode, Claude Code, Cursor, etc.) a persistent, shared memory via `search_memory`, `add_memory`, and `delete_memory` tools.
- **Lazy-Loaded PyTorch**: Instant server boot times (less than 4s). AI models only load into RAM when a memory operation is explicitly requested.
- **Realtime 3D Visualizer**: A sleek local web application that maps your project's memory as a glowing, interactive neural network.
- **Neo4j Aura Ready**: Directly offloads graph storage and vector queries to Neo4j Cloud, meaning it works on any machine without local database installation.
- **100% Secure**: Credentials are kept entirely out of the code using `.env` files, ensuring your database passwords are never leaked to GitHub!

## 🚀 Quick Start (Local Setup)

1. **Clone the Repository**
   ```bash
   git clone https://github.com/mmyahya29/MCP-Visualizer.git
   cd MCP-Visualizer
   ```

2. **Configure your Database Credentials**
   Rename the `.env.example` file to `.env` and insert your Neo4j Cloud credentials:
   ```env
   NEO4J_URI=neo4j+s://...
   NEO4J_USERNAME=neo4j
   NEO4J_PASSWORD=your_password
   ```

3. **Launch the Visualizer!**
   - **Windows:** Double-click `run.bat`
   - **Mac/Linux:** Run `./run.sh`
   
   *This automatically sets up your Python virtual environment, installs the requirements, and opens the 3D visualizer at `http://localhost:8000`.*

## 🤖 Connecting to your AI Agents (MCP Setup)

To give your AI coding agents access to this brain, configure them to use this repository as a local MCP server.

**For Antigravity:**
Add the following to your `~/.gemini/config/mcp_config.json`:
```json
"mcpServers": {
  "foster-memory": {
    "command": "/absolute/path/to/MCP-Visualizer/venv/Scripts/python.exe",
    "args": [
      "/absolute/path/to/MCP-Visualizer/server.py"
    ]
  }
}
```
*(Mac/Linux users: change `venv/Scripts/python.exe` to `venv/bin/python`)*

**For OpenCode:**
Add the following to your `~/.config/opencode/opencode.json`:
```json
"mcp": {
  "foster-memory": {
    "type": "local",
    "command": [
      "/absolute/path/to/MCP-Visualizer/venv/Scripts/python.exe",
      "/absolute/path/to/MCP-Visualizer/server.py"
    ],
    "enabled": true
  }
}
```

## 🌐 Deploying to Vercel
If you want to host your 3D Visualizer permanently on the internet:
1. Copy the contents of the `VercelVisualizer` folder into a new GitHub repository.
2. Go to Vercel.com and deploy that specific repository.
3. In your Vercel Dashboard, add your `NEO4J_URI`, `NEO4J_USERNAME`, and `NEO4J_PASSWORD` environment variables.

---
*Built to make your AI tools smarter.*