Guide / AI Product Interface
It is a controlled product surface that lets an AI host find information and complete approved tasks for a user.
↓Definition
The AI host receives named tools with clear inputs. Your product verifies the user, applies its rules, performs the action, and returns a result the person can understand.
MCP tools specificationUsage
OpenAI's 2025 usage study analyzed 1.5 million privacy-preserving ChatGPT conversations and reported 700 million weekly users in mid-2025. The interface has scale. An individual product still has to earn demand.
OpenAI · How people use ChatGPTCustomer signal
Adobe reported that generative AI traffic to US retail sites increased 1,300% year over year during the 2024 holiday season. In its survey of 5,000 US consumers, 7 in 10 respondents who had used generative AI for shopping said it enhanced their experience. Adobe also noted that the user base remained modest.
Adobe · AI shopping researchFit
Good first workflows combine a few existing product steps and end with a result that can be confirmed. Avoid broad assistant promises with no bounded action.
Hosts
ChatGPT Apps, Claude integrations, Gemini surfaces, and coding agents evolve separately. An open MCP core reduces duplicate product work, but each host still needs its own verification.
OpenAI · MCP Apps compatibilityFirst decision
Before choosing technology, write one sentence: this user can ask for this result, using this data, with this approval. That sentence is the first interface contract.
Official guide to MCP servers, tools, authentication, and UI for ChatGPT apps.
Protocol reference for named, discoverable tools and their input and output contracts.
Primary product announcement for apps and the Apps SDK in ChatGPT.
AI / Second opinion
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.
No. The MCP layer is one part. We also scope the product actions, permissions, host-specific behavior, UI, testing, and release path.
Usually no. The interface sits in front of approved capabilities in your existing product. We start with a narrow workflow and expand from evidence.
The shared architecture can support all three. Each host still has its own UI, authentication, approval, and publishing rules, so we verify them separately.
We define explicit tools, validate inputs, keep user approval visible, and preserve the product's existing authorization rules.