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Banking Model Context Protocol Server

by Abhinav-pyth

Banking Chatbot with MCP Integration

A sophisticated banking chatbot application that uses Azure OpenAI and Model Context Protocol (MCP) for secure and efficient message handling.

Features

  • AI-Powered Banking Assistant: Uses Azure OpenAI to provide intelligent responses to banking queries
  • Model Context Protocol (MCP): Implements a secure message communication protocol
  • Real-time Chat Interface: Modern, responsive UI for seamless user interaction
  • Comprehensive Logging: Detailed logging system for monitoring and debugging
  • Bank Information Integration: Dynamic display of bank details and services
  • Markdown Support: Rich text formatting for responses

Project Structure

. ├── app.py # Main Flask application ├── mcp_server.py # MCP server implementation ├── mcp_client.py # MCP client implementation ├── requirements.txt # Python dependencies ├── .env # Environment variables ├── templates/ # HTML templates │ └── index.html # Chat interface └── logs/ # Log files ├── client_messages.log ├── mcp_client.log └── mcp_server.log

Prerequisites

  • Python 3.8 or higher
  • Azure OpenAI API access
  • Required Python packages (see requirements.txt)

Installation

  1. Clone the repository:
    git clone <repository-url> cd banking-chatbot
  2. Create and activate a virtual environment:
    python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
  3. Install dependencies:
    pip install -r requirements.txt
  4. Create a .env file with your credentials:
    ENDPOINT_URL=your_azure_endpoint AZURE_OPENAI_API_KEY=your_api_key DEPLOYMENT_NAME=your_deployment_name

Usage

  1. Start the MCP server:
    python mcp_server.py
  2. In a new terminal, start the Flask application:
    python app.py
  3. Access the chatbot interface at http://localhost:5000

MCP Protocol

The Model Context Protocol (MCP) is implemented to handle message communication between the chatbot and the server. It provides:

  • Secure message transmission
  • Message queuing and reliability
  • Detailed logging
  • Real-time message handling

Message Types

  • Chat Messages: User queries and AI responses
  • System Messages: Administrative and control messages

Logging

The application maintains detailed logs in the logs directory:

  • client_messages.log: Chat message history
  • mcp_client.log: Client connection and operation logs
  • mcp_server.log: Server operation logs

Bank Information

The chatbot is configured with comprehensive bank information including:

  • Business hours
  • Branch locations
  • Available services
  • Contact information
  • Support channels

Development

Adding New Features

  1. Update the BANK_INFO dictionary in app.py for new bank information
  2. Modify the SYSTEM_MESSAGE for updated AI behavior
  3. Add new message handlers in mcp_client.py for additional functionality

Testing

Run the test client to verify MCP functionality:

python test_client.py

Clear logs for testing:

python clear_logs.py

Security

  • API keys and sensitive information are stored in .env
  • MCP provides secure message transmission
  • Input validation and error handling are implemented

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

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security - not tested
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license - not found
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quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Implements a secure message communication protocol for handling exchanges between the banking chatbot and Azure OpenAI, providing message queuing, reliability, and detailed logging.

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