Frequently Asked Questions (FAQ)

Q: What is the Model Context Protocol (MCP)? A: MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). In this banking chatbot, MCP ensures secure and reliable message communication between the chatbot interface and the backend server.

Q: How does the chatbot use Azure OpenAI? A: The chatbot utilizes Azure OpenAI for natural language understanding and generation. This allows the chatbot to understand user queries, process them, and generate relevant and helpful responses.

Q: What kind of bank information can the chatbot provide? A: The chatbot is configured to provide comprehensive bank information, including business hours, branch locations, available services, contact information, and support channels. This data is dynamically displayed to users.

Q: How secure is the communication between the chatbot and the server? A: Communication is secured using the Model Context Protocol (MCP), which provides encryption, authentication, and message integrity to protect sensitive customer data.

Q: What are the prerequisites for running this chatbot application? A: The prerequisites include Python 3.8 or higher, access to the Azure OpenAI API, and the necessary Python packages listed in the requirements.txt file.

Q: How do I install the required dependencies? A: You can install the dependencies by running pip install -r requirements.txt in your virtual environment after cloning the repository.

Q: Where are API keys and other sensitive information stored? A: API keys and sensitive information are stored in a .env file to ensure they are not exposed in the codebase. It’s important to properly secure this file.

Q: Can I customize the chatbot with additional features? A: Yes, you can customize the chatbot by updating the BANK_INFO dictionary in app.py, modifying the SYSTEM_MESSAGE for AI behavior, and adding new message handlers in mcp_client.py.

Q: How can I test the MCP functionality? A: You can test the MCP functionality by running the test_client.py script. This will verify that messages are being sent and received correctly.

Q: What kind of logging does the application support? A: The application maintains detailed logs in the logs directory, including chat message history, client connection logs, and server operation logs.

Q: What is UBOS, and how does it relate to this chatbot? A: UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. While this chatbot is a specific application, UBOS provides a broader platform for building, orchestrating, and connecting AI agents with enterprise data.