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MCP Apps: Putting Your Brand's Service Inside ChatGPT and Claude

For years, companies building digital services had three main options: a website, an app, or a custom system. In 2026 there is a fourth venue: the AI chat tools people already use every day. In January, MCP Apps, driven jointly by Anthropic and OpenAI, became the first official extension to the Model Context Protocol (MCP). It lets companies place interactive interfaces they design themselves directly inside tools like ChatGPT and Claude. For brands considering custom development, this is more than a new piece of jargon. It is a new channel worth evaluating seriously.

What MCP Apps are: from answers to interfaces inside the chat

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MCP is the open standard that lets AI assistants connect to external tools and data. Until recently, an AI could use MCP to look things up or call a service, but the result was usually just text or a table, laid out however the AI decided.

MCP Apps fill in the interface layer. A company's MCP server can return an interactive view it designed itself, such as a form, a dashboard, a product picker or a multi-step flow, which ChatGPT or Claude renders inside a sandboxed iframe. According to the official MCP blog, the extension went live on 26 January 2026, building on the earlier MCP-UI project and the OpenAI Apps SDK. The new MCP specification released on 28 July formally brought MCP Apps into its extensions framework, and actions taken in the interface pass through the same authorization path as tool calls.

Put simply: the AI understands what the user wants, and your interface presents the information accurately, beautifully and in a way people can act on.

Why MCP Apps are a new option for custom development

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In Custom software or SaaS? we argued that custom work is worth it when it creates differentiation off-the-shelf tools cannot. MCP Apps add three new kinds of differentiation:

  • Show up where users already are: no app download and no website visit. Users can look up, book or compare without leaving the conversation.
  • Build once, run on several platforms: because it is an open standard, the same MCP App can work across supporting environments such as ChatGPT, Claude and VS Code, instead of one build per platform.
  • Your interface is not rewritten by the AI: plain-text answers are improvised by the model and details can go wrong. With your own interface, the brand decides how data is displayed and where every button sits.

This echoes a trend we covered earlier: AI shopping agents are changing how people find information and make decisions, so brands now need to design experiences for both humans and AI.

Which brands should move first

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Not every brand needs to jump in right away. MCP Apps pay off most clearly in these situations:

  • Services that need interaction to convert: quotes, booking slots, plan comparisons. These are tiring as back-and-forth text and far smoother with a small interface.
  • Data-driven products: companies with inventory, pricing, specifications or membership data can let the AI query it and present it in a consistent format.
  • Internal tools: if your team already works in Claude or ChatGPT, plugging internal lookups and approvals into it is often easier to adopt than yet another back office.

On the other hand, if your business is driven mainly by brand story and emotional connection, your website and content remain home base, and MCP Apps can wait.

Four things to settle before building MCP Apps

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  1. Start with the least privilege: begin with read-only queries, then open up write actions gradually. Decide at design time which actions the AI may trigger on its own and which always require the user to confirm.
  2. The interface is your brand too: inside someone else's platform, space is tight, so type size, color and interaction rhythm need even more precision. This is a design skill, not just an engineering one.
  3. Your data must be trustworthy: the AI answers questions based on what your tools return. Stale or wrong data damages brand credibility.
  4. The specification will keep evolving: the new MCP specification introduces a deprecation policy with at least 12 months between a feature being deprecated and removed. You can invest with confidence, but someone needs to own long-term maintenance.

The division of labor is clear here as well:

  • AI handles: understanding intent, calling the right tools, chaining steps together.
  • People handle: deciding which services belong in the conversation, designing the interface and brand experience, and guarding permissions and data quality.

Conclusion

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MCP Apps push the definition of custom development one step further. You are no longer only building a website or a system; you are designing how your brand shows up inside the conversation between a user and an AI. The technical barrier is falling, and the real difference will come down to what you build and how beautiful and useful it is. AI delivers perfection; people deliver emotion. If you want to assess whether your services are a good fit for MCP Apps, explore TitApeX services or talk to us.

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