Collaborative aircraft design environments face significant challenges in intuitive geometry manipulation and tool integration. This research develops an AI-assisted interface using the Model Context Protocol (MCP) to bridge natural language commands with established aerospace tools. The approach integrates large language models with three specialized applications for optimization, visualization, and aircraft geometry modification. Results demonstrate successful implementation, enabling designers to accomplish complex tasks such as multi-objective optimization and empennage reconfiguration through conversational prompts. While occasional AI misinterpretations required prompt refinement, the system proved effective at translating intent into precise tool operations. The study concludes that MCP provides a viable framework for creating intuitive design interfaces while maintaining accuracy via integration with domain-specific computational methods.