How to Build an Embedded ChatGPT App (MCP App) (sunpeak.ai)

A recent article delves into practical insights for building embedded ChatGPT applications, highlighting three crucial lessons learned from hands-on experience. The first key takeaway emphasizes the importance of embracing the Modular Component Pattern (MCP) when architecting applications. The author clarifies that while the official documentation may imply that ChatGPT Apps utilize MCP, the correct approach is to align app design entirely with MCP principles, treating each UI component as a Resource and every API as a Tool. This understanding can prevent significant issues during production deployment. The second lesson concerns cache invalidation, noting that users must update their Resource URIs and refresh the app connection within ChatGPT after any changes to ensure the latest version is in use. Lastly, the article reveals that the official OpenAI documentation only covers about two-thirds of the available runtime API, hinting at additional undocumented features that developers can leverage. The author warns that many example apps may not utilize these potential capabilities effectively and encourages experimentation with an open-source local ChatGPT simulator to facilitate iterative development. These insights are valuable for developers looking to optimize their ChatGPT Apps and utilize the full breadth of API capabilities.