Frequently Asked Questions about the Attendance Management MCP Server

Q: What is an MCP Server? A: MCP stands for Model Context Protocol. An MCP Server acts as a bridge, standardizing how applications provide context to Large Language Models (LLMs). It allows AI models to access external data sources and tools, enabling more informed decision-making.

Q: What are the key features of the Attendance Management MCP Server? A: Key features include employee information management, attendance record tracking, leave request management, overtime request management, schedule management, and comprehensive statistics and reports.

Q: What are the prerequisites for installing the Attendance Management MCP Server? A: The prerequisites include Python 3.10 or higher and a Neon PostgreSQL database.

Q: How do I install the Attendance Management MCP Server? A: Installation involves cloning the repository, setting up a virtual environment, installing dependencies, and configuring the database connection using a .env file.

Q: How do I run the Attendance Management MCP Server? A: You can run the server using the provided wrapper script (./run_mcp.sh) or by activating the virtual environment and using the MCP CLI (mcp run attendance_mcp_server.py).

Q: How do I use the server with Claude Desktop? A: To use the server with Claude Desktop, install Claude Desktop, run the provided installation script (python install_claude_desktop.py), and restart Claude Desktop.

Q: What do I do if I encounter a “No module named ‘mcp’” error? A: Ensure the MCP package is installed in the Python environment that Claude Desktop is using. You can try running ./install_dependencies.sh and checking the Claude Desktop logs for more information.

Q: What tools are available in the Attendance Management MCP Server? A: Available tools include methods for managing employee information (e.g., get_employee_info, list_employees), attendance records (get_attendance_records, submit_attendance_record), leave management (get_leave_requests, submit_leave_request), overtime management (get_overtime_requests, submit_overtime_request), schedule management (get_employee_schedule, list_shifts), and statistics and reports (get_monthly_attendance_stats).

Q: What resources are available? A: Available resources include employee://{employee_id} for employee information, department://{department_id} for department information, and attendance://{employee_id}/{date} for attendance information.

Q: What prompts are available? A: Available prompts include request_leave, request_overtime, and check_attendance.

Q: How does the Attendance Management MCP Server integrate with UBOS? A: The server seamlessly integrates with UBOS, a full-stack AI Agent development platform, providing a centralized platform for managing and orchestrating AI Agents, connecting them with enterprise data, and building custom AI Agents with your LLM model and Multi-Agent Systems.