Developed a dynamic server configuration feature for the pydantic/pydantic-ai repository, focusing on enhancing deployment flexibility and security. The work enabled environment variable expansion within the mcp.json configuration file, allowing load_mcp_servers() to reference environment variables directly or use default values. This approach reduced manual configuration steps and improved the handling of sensitive information across different environments. The implementation leveraged Python for backend development and incorporated robust testing practices to ensure reliability. By supporting dynamic configuration through environment variables, the solution streamlined deployment workflows and aligned with best practices for secure, maintainable backend systems in Python-based projects.