ChatGPT App Development

Put your product inside ChatGPT.

Q: Is a ChatGPT app the same as an OpenAI plugin?

On this site, `ChatGPT app` means the end-user experience delivered through an OpenAI plugin. In OpenAI's current product model, the installable package is a plugin. A plugin can contain skills, an MCP server, or both, and its MCP server may return optional UI resources.

KNWN builds OpenAI plugins that let people use your live product from ChatGPT and supported Codex surfaces. We design the user journey, package the required skills and MCP tools, connect accounts, add UI when it improves the task, test the complete experience, support submission, and hand over the source and deployment. Each target surface is defined and tested separately because availability and capabilities can differ.

Discuss your build

One-off projectClient-owned code and infrastructureNo required KNWN hosting

This is not a mobile app that copies ChatGPT and it is not a chatbot trained on your website. It is a product integration that can use your live systems and complete controlled actions.

Let users discover and use your product without leaving the conversation.

A useful ChatGPT app does more than answer questions about your company. It gives the user a direct path into the capabilities your product already provides.

Examples

Find products, services, records, or options that match a request
Compare live choices using current data
Check availability, pricing, status, eligibility, or account information
Prepare a quote, reservation, order, ticket, or update
Connect an existing customer account
Review a proposed action in a form, table, or comparison view
Confirm an approved write and receive a clear result
Continue at the correct authenticated page in your product when needed

What a ChatGPT app contains

One plugin package, shaped around the workflow.

On this site, ChatGPT app means the end-user experience delivered through an OpenAI plugin. In OpenAI's current product model, the installable package is a plugin. A plugin can contain skills, an MCP server, or both, and its MCP server may return optional UI resources.

KNWN chooses the smallest package that supports the job instead of adding technical layers the user will never need.

Skills

Instructions and supporting resources that help the model follow a repeatable workflow using the capabilities already available to it.

MCP server

Controlled tools that connect the plugin to your live data, accounts, and business actions.

Optional UI using the MCP Apps standard

UI resources returned by selected MCP tools for workflows that benefit from comparison, editing, confirmation, or navigation. The tools remain useful without UI because component rendering depends on host support. ChatGPT implements the MCP Apps standard, and portability to another host must be tested.

The integration is designed from the request to the completed result.

1. Recognition

The plugin and tool metadata make the supported jobs clear so the correct capability can be selected for relevant requests.

2. Account connection

If the task needs private data or actions, the user connects an account and grants the permissions required for the approved scope.

3. Read or prepare

The plugin retrieves live information or creates a draft without committing a consequential action too early.

4. Inspect and confirm

The user reviews the important details in conversation or an interface and confirms when the action requires approval.

5. Execute and recover

The final tool executes through your backend, returns a clear result, and provides a useful recovery path if the action cannot be completed.

Use chat for language. Use UI when structure matters.

A custom component is useful when the user needs to compare multiple options, edit structured fields, inspect a schedule, review a cart or quote, confirm a consequential action, or navigate a result. It is unnecessary when a concise model response or structured result already communicates the outcome.

Possible components

Product or inventory comparison
Editable quote or booking summary
Availability selector
Account status panel
Map or location result
Approval and confirmation form
Order, case, or task progress view

KNWN keeps the underlying tools useful without the component so the workflow can still operate when a client does not render the custom UI.

A good app has to be selected for the right request

We treat metadata as product behavior, not launch copy.

Tool names and descriptions influence when a capability is selected and how it is used. KNWN writes them around the user intent, then evaluates them with requests that should trigger the tool, indirect requests that should still be understood, and similar requests that should not trigger it.

We review:

Plugin name, description, and purpose
Tool names and descriptions
Input field names and guidance
Read and write classifications
Confirmation requirements
Direct, indirect, and negative test requests
Behavior when required information is missing
Results with and without the optional interface

The plugin should know who the user is and still enforce what they may do.

When a plugin connects to an external user account, KNWN implements the applicable OAuth 2.1 authorization-code flow with PKCE, protected-resource and authorization-server discovery, and per-tool security declarations. Your backend validates token audience and scopes and enforces authorization on every tool call. Authentication identifies the caller but does not replace tenant, role, object-level, or business-rule checks.

Controls can include:

User account connection
Narrow scopes
Tenant isolation
Token validation and revocation behavior
Read, draft, and write separation
Explicit confirmation before consequential actions
Idempotency and duplicate-action protection
Audit events and operational logs

We prepare the complete build for review. We do not sell a promise of approval.

KNWN can package the plugin, test it in the agreed supported surfaces, prepare metadata and policy information, assemble submission materials, respond to technical feedback, and support the launch process.

Approval, placement, discovery, and distribution remain under OpenAI's control. For public submission, the publisher must have a verified developer or business identity, the submitter must have the required access in that publisher's OpenAI organization, and any MCP server must use a stable, publicly reachable HTTPS endpoint. KNWN can prepare the implementation and review materials and can submit when the client grants the required role. The client supplies and approves its legal, privacy, terms, support, regional, and test-account information.

A complete plugin build and handover can include

Use-case and user-journey definition
Plugin package and configuration
Skills and supporting resources when useful
Remote MCP server and tool surface
Input and output schemas
Authentication and authorization
Optional UI using the MCP Apps standard
Tool and plugin metadata
Direct, indirect, and negative evaluations
Failure and safe-action tests
Privacy, support, and submission materials
Client-controlled deployment
Source repository, documentation, and runbook
Submission and technical review support

Your app should not depend on a permanent KNWN subscription.

KNWN hands over the source, deployment configuration, plugin assets, tests, evaluation scenarios, and operating documentation included in the scope. Production infrastructure can remain in accounts your team controls. KNWN hosting is not required.

Review security and handover

The visible component is only one part of the build.

Scope is shaped by:

Number of user journeys and tools
API and authentication readiness
Public versus private account data
Read-only versus state-changing actions
Tenant and permission complexity
Skills and supporting resources
Need for a custom UI component
Target supported surfaces
Evaluation and security depth
Packaging, submission, and review work
Deployment environment and internal approvals

Unless explicitly included, ChatGPT app development does not include a mobile app that imitates ChatGPT, a generic website chatbot, a complete standalone agentic application, reconstruction of the client's backend, indefinite infrastructure operation, unlimited review cycles, or guaranteed approval, discovery, installation, and invocation.

Frequently asked questions

Is a ChatGPT app the same as an OpenAI plugin?

Does every plugin need an MCP server?

No. A skills-only plugin may be enough when instructions and existing tools can complete the workflow. An MCP server is appropriate when the plugin needs to connect to your service, authenticate users, access live data, expose controlled actions, or run server-side behavior.

Does every app need a custom interface?

No. We add UI only when it materially improves comparison, editing, confirmation, navigation, or another structured interaction. The tools should remain useful without the component.

Can users connect their existing account?

Yes, when the product and approved architecture support account connection. We implement the authorization flow and map the granted identity and scopes into the permissions enforced by your backend.

Can the app take write actions?

Yes, if the backend supports them and the risk is controlled. We separate drafts from committed writes, validate inputs, preserve permission checks, add confirmation where required, and test duplicate and partial-failure cases.

Do you guarantee approval or discovery?

KNWN can prepare, test, package, document, and support the submission. When the client grants the required role in its verified publisher organization, KNWN can also submit through that organization. OpenAI reviews the submission, and the publisher controls publication after approval. Approval, placement, and discovery cannot be guaranteed.

Who owns the final implementation?

The client receives the source repository, deployment configuration, documentation, and agreed assets. The build can run in client-controlled infrastructure without required KNWN hosting.

What should someone be able to do with your product from ChatGPT?

Bring us the user request, the systems behind it, and the action that should happen. We will define whether the right plugin needs skills, an MCP server, an interface, or a combination of them.

Discuss your build