🛡️ SecureLife Claims Processing Hub

An asynchronous, distributed AI agent pipeline for processing insurance claims. This project uses a modern two-tier architecture:

1. Model Context Protocol (MCP) Server: A remote data layer exposing SQLite database operations over streamable_http.
2. LangGraph + Chainlit Client: A conversational UI powered by a LangGraph multi-agent workflow that sanitizes inputs, evaluates fraud, verifies documents, and logs immutable audits via the MCP server.

---

📁 Project Structure

/securelife_project
├── SecureLife_claims.db           # SQLite Database
├── README.md                      # Project documentation
├── securelife_mcp_server/         
│   └── server.py                  # FastMCP Data & Tools Server
└── securelife_client_app/
    ├── .env                       # Environment variables (API Keys)
    ├── requirements.txt           # Python dependencies
    ├── agent.py                   # Decoupled LangGraph & MCP Client Logic
    └── app.py                     # Chainlit UI implementation

---

🚀 Getting Started

These instructions are tailored for Windows users running VSCode with PowerShell or Command Prompt.

1. Prerequisites (Python 3.12)

This project is optimized for Python 3.12. If you do not have it installed, open your terminal and install it via the Windows Package Manager (winget):

winget install -e --id Python.Python.3.12

Note: You may need to restart your terminal or VSCode after installation.

---

2. Create and Activate the Virtual Environment

Navigate to the root directory of the project (securelife_project) in your terminal.

Create the environment using the Python launcher to force version 3.12:

py -3.12 -m venv .venv

Activate the environment:

• If using PowerShell:

.\.venv\Scripts\Activate.ps1

(If you receive an execution policy error, run Set-ExecutionPolicy RemoteSigned -Scope CurrentUser first).

• If using Command Prompt (cmd):

.\.venv\Scripts\activate.bat

You should now see (.venv) at the start of your terminal prompt.

---

3. Install Dependencies and Setup Environment

With your virtual environment activated, navigate to the client application folder and install the required packages.

pip install -r requirements.txt

Run this from the repository root — that is where requirements.txt lives.

Next, configure your environment variables. In the repository root, copy .env.example to .env and fill it in. load_dotenv() searches upward from the working directory, so one file at the root serves both processes:

OPENAI_API_KEY=your_openai_api_key_here

# Optional — every one of these has a working default.
# SECURELIFE_DB_PATH=/abs/path/SecureLife_claims.db         # default: repo root
MCP_ENDPOINT_URL=http://127.0.0.1:8765/mcp                  # where the client looks