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What happens next
A direct scope conversation.
We review the product and workflow, flag missing decisions, and tell you whether discovery or a build scope is the right next step.
Contact / Project brief
START WITH ONE CUSTOMER TASK
Send the product, user, and action. We will help define the smallest useful interface.
↓Evidence / Primary sources
OpenAI · Apps SDK
Official guide to MCP servers, tools, authentication, and UI for ChatGPT apps.
Model Context Protocol · tools specification
Protocol reference for named, discoverable tools and their input and output contracts.
Model Context Protocol · authorization
Protocol reference for authorization responsibilities at the connection boundary.
AI / Second opinion
Ask your AI first.
Use this prepared question to assess where an AI Product Interface could remove friction from your product.
“I run a software product. Help me identify one high-value workflow customers could complete through an AI Product Interface. Ask me about the product, the user, the action, required data, permissions, and the safest small first release.”
The prompt is copied as a backup. Some AI hosts may ask you to paste it after sign-in.
FAQ04
Questions, answered.
Is this only an MCP server?
No. The MCP layer is one part. We also scope the product actions, permissions, host-specific behavior, UI, testing, and release path.
Do we need to rebuild our product?
Usually no. The interface sits in front of approved capabilities in your existing product. We start with a narrow workflow and expand from evidence.
Will it work in ChatGPT, Claude, and Gemini?
The shared architecture can support all three. Each host still has its own UI, authentication, approval, and publishing rules, so we verify them separately.
How do you keep actions safe?
We define explicit tools, validate inputs, keep user approval visible, and preserve the product's existing authorization rules.