Insights / Product decisions
Build the right interface first
Clear product choices matter more than the number of AI hosts on your roadmap.
Practical guidance for founders and product teams adding an MCP for ChatGPT, Claude, and Gemini.
- Works in
- ChatGPT
- Claude
- Gemini
- Coding agents
The collection01
Read the decisions behind the build.
Where your product's boundary sits, what each host needs on its own, and which operating model fits. Every claim links to its source inside the article.
01 / Guide
What is an AI Product Interface?
A plain-language guide to actions, permissions, confirmations, and per-host work.
Open the page02 / ChatGPT / MCP
Three decisions before you build
Pick the user job, keep your product's boundary, and plan the release work each host needs.
Open the page03 / B2C / Enterprise
Different apps need different promises
Compare Prostir Build's B2C product role with a private, governed enterprise workflow.
Open the pageResearch notes02
Use named sources. Keep claims narrow.
Use official platform documentation and named market research. A directional signal is not a promise of customer demand.
Where this comes from.
OpenAI · Apps in ChatGPTPrimary product announcement for apps and the Apps SDK in ChatGPT.OpenAI · Apps SDKOfficial guide to MCP servers, tools, authentication, and UI for ChatGPT apps.Model Context Protocol · tools specificationProtocol reference for named, discoverable tools and their input and output contracts.AI / Second opinion03
Not sure where to start? Ask an AI.
Paste this question into ChatGPT, Claude, or Gemini. It walks you through finding the one task your customers would most want to finish by chatting, instead of clicking through your app.
“I run a software product. Help me identify one high-value workflow my customers could finish inside ChatGPT instead of switching between tabs. Ask me about the product, the user, the action, the data it needs, permissions, and the safest small first release.”
The prompt is copied as a backup. Some AI chats may ask you to paste it after sign-in.
FAQ04
Questions, answered.
Is this just an MCP server?
No. The server is one piece. We do the whole job: we pick the customer task, set who can do what, handle the quirks of each AI chat, make the actions run fast, add monitoring, test it, and ship it.
Do we have to rebuild our product?
Almost never. Our layer sits in front of what your product already does. We start with one small workflow and grow from what works.
Will it work in ChatGPT, Claude, and Gemini?
The same build can serve all three. Each one has its own sign-in, look, approval step, and publishing rules, so we set up and test each one separately.
How do you keep it safe?
Your product decides what is allowed, and we keep that in charge. Every action is spelled out, every input is checked, and the customer sees an approval step before anything happens. Our layer sits beside your product, not inside it.
Where does it run? Does it touch our code?
It runs as a separate service in front of your product. It never goes into your code, and you still own your data.
What does it cost, and how fast?
A first workflow starts at €3,200 and goes live in about 7 days.
Contact us05
Start with one customer task
Send us your product, who uses it, and the action you have in mind. We will tell you the smallest version worth building, and whether it is a €3,200 first workflow or something that needs a closer look first.