🧠 Jeneen's MCP Agent

This project is a multi-functional AI agent built using FastMCP. It includes:

• ✅ An Arabic legal chatbot that answers common legal questions.

• 🔍 A Google search tool.

• 🧬 A Variational Autoencoder (VAE) model that generates handwritten digit images.

📁 Project Structure

├── main.py # Main script to run the MCP agent ├── chatbot.py # Arabic legal chatbot logic ├── vae_model.py # VAE model definitions (Encoder, Decoder, VAE) ├── output/ # Model checkpoints and generated images ├── data/ # MNIST dataset (auto-downloaded) ├── VAE.ipynb # Jupyter notebook for training the VAE model └── README.md # This documentation file

Related MCP server: Deep Research MCP Server

⚙️ Available MCP Tools

1. legal_chat(query: str) → str

Arabic-language chatbot that responds to legal questions such as:

• Annual leave

• Divorce

• Custody

• Employment rights

• Rental agreements Example: { "tool": "legal_chat", "input": "ما هي حقوقي في حال الطلاق؟" }

2. search_google(query: str) → str

Opens a Google search in the default browser. Example: { "tool": "search_google", "input": "قانون العمل الأردني" }

3. vae_generate(n_images: int) → str

Generates handwritten digit images using a trained VAE model. Returns a base64-encoded PNG image. Example: { "tool": "vae_generate", "input": { "n_images": 8 } }

How to Run Create and activate a virtual environment python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate

Install dependencies pip install -r requirements.txt (Optional) Train the VAE model using VAE.ipynb Or use the pre-trained model in: output/vae_epoch_50.pth

Run the MCP agent python main.py