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MCP and business systems

Get Your Product into ChatGPT and Claude: Apps SDK and MCP

To let people use your product or data inside ChatGPT and Claude, expose a useful task through an MCP server and connect it to the chosen AI clients. ChatGPT can also display an optional interface alongside the conversation. Directory publication is a separate step, with platform-specific requirements and review.

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What an MCP server does for your business

Your customer knows what they want, but your product catalogue lives in another application. An MCP server can give their AI assistant a defined way to search that catalogue, inspect a result or check stock. Your existing system remains responsible for the records and business rules.

MCP means Model Context Protocol. The official introduction describes an open standard for connecting AI applications to external systems. The server exposes capabilities called tools, such as search_products, with defined inputs and outputs. The AI client calls the appropriate tool during a conversation.

A useful starting point is a task someone already performs in your product. “Find a desk lamp available in my city” is specific enough to design and test. “Put our business into AI” leaves the user, the data and the expected result undefined.

How a request reaches your product data

Consider a lighting retailer. A connected customer asks: “Is the black desk lamp available in the city-centre store?”. The assistant identifies the product and calls a stock tool. The MCP server checks access and requests the current quantity from the inventory system. The assistant then turns that result into an answer.

01 / A stock lookup

  1. REQUESTChatGPT or ClaudeSelects the stock tool and supplies a product code.
  2. CONTROLMCP serverChecks the user and the permitted operation.
  3. SOURCEInventory systemReturns current stock for the selected store.
  4. RESULTAnswer in chatThe assistant explains the returned information.
Results return through the same connection; internal fields do not belong in the public stock response.

The tool should distinguish “product not found”, “out of stock” and “inventory service unavailable”. They lead to different customer decisions. A stale answer copied from an earlier conversation cannot stand in for a successful stock check.

Reserving the lamp adds a write operation. It needs a clear confirmation and protection against duplicate execution when a request is retried. Those controls belong in your server and business system. A reassuring sentence from the model cannot prevent a second reservation.

MCP versus an existing API

An API is the interface other software uses to interact with your system. Your MCP server will often call that API, then expose selected operations in a form AI clients can discover and use. An existing inventory API is therefore a useful foundation.

For a routine connection between a store and an accounting system, a direct API integration may solve the whole problem. MCP becomes useful when the interaction happens through an AI assistant. It adds a common connection format; it does not create access to software that has no suitable integration route.

Our MCP server development starts by checking the existing API, the desired task and the permissions. The answer may be one small tool around an existing endpoint. That is a better first release than exposing every operation your backend supports.

02 / Shared server, separate client checks

ChatGPT · Claude · Cursor

Each client discovers tools and presents results in its own way.

One MCP server

Shared operations, authentication, permissions and quotas.

Your systems

Catalogue, orders or archive. Each keeps its own business rules.

A common protocol makes reuse possible. A passing test in one assistant does not establish compatibility with every other client.

OpenAI Apps SDK and apps in ChatGPT today

The OpenAI Apps SDK supports building apps with tools and interfaces inside ChatGPT.

The practical decision is whether your task needs a visual interface. A plain stock lookup can return structured information. A customer choosing among products may benefit from result cards and a selection control. OpenAI's current UI guide makes UI optional and describes the open MCP Apps standard for interfaces returned by an MCP server.

Keep tools useful when a client does not display the component. A booking tool should still return the selected date and status in a usable form. We scope ChatGPT app development around the customer task first, then the interface that helps someone complete it.

Connecting your service through a Claude connector

A Claude connector lets Claude interact with an outside service. Users can choose a directory connector or add a custom connection. Anthropic's custom remote MCP guide explains the latter route. It is useful for testing your own service with selected users before wider distribution.

A remote MCP server runs on service infrastructure and is reached over the network. A local server runs on a user's computer. The MCP architecture guide distinguishes these arrangements. For a customer-facing product, a hosted remote service is usually the practical starting point.

We built an MCP server used from Claude, ChatGPT and Cursor, with OAuth 2.1 sign-in and per-client quotas. We check how each assistant selects tools, handles errors and uses the returned data. Tool descriptions and predictable responses matter as much as the connection opening successfully.

OAuth, customer permissions and quotas

OAuth 2.1 lets a person authorise access through their account. The client receives a token representing that access. The MCP authorization specification describes the mechanism for protected HTTP connections. Your application must still determine which records and actions the user is allowed to access.

A customer asking for an order must receive their own order. A public stock tool should not return wholesale costs or customer contact details. Enforce those boundaries on the server for every call. A shared service credential needs particular care because it can expose everything that credential can reach.

Quotas limit usage and contain downstream API costs. Decide what happens when a quota is reached, how access is revoked and which request details are logged. In a small first release, a read-only tool with explicit limits is often enough to establish whether customers use the integration.

ChatGPT apps directory and Claude connectors directory

A working private connection and a public directory listing are separate deliverables. OpenAI's submission guide describes review, approval and a publication step after approval.

The Claude connectors directory helps users discover integrations. Anthropic's connector guide explains directory discovery and custom connections. Adding your own server by URL does not automatically make it a public listing. Check the current submission route when the service is ready.

03 / From a useful tool to distribution

  1. FIRST RELEASESelected usersOne task with real permissions and test records.
  2. VALIDATIONEach AI clientSign-in, results, failures and denied access.
  3. DISTRIBUTIONDirectory reviewA separate process under the platform's current rules.

What to prepare for a useful first release

Choose a question with a reliable source and a verifiable answer: stock by product code, the status of the user's own order, or a document search. Define a successful result and an access-denied case. Give the developer API documentation, a test environment and someone who can check the returned information.

Ask for development, hosting, external usage and ongoing maintenance to be scoped separately. The number of systems, available APIs and write operations determine the work. Directory submission should also be named explicitly if it is part of the brief.

If the useful answer is inside manuals or policy documents, read what RAG is and how document retrieval works. MCP can expose the search tool to an assistant; RAG supplies relevant passages for its answer.

Frequently asked questions

What is an MCP server?

An MCP server is a program that exposes data and capabilities through the Model Context Protocol. An AI application can discover and call those capabilities, subject to the access rules implemented by the service.

Is OpenAI Apps SDK the same as MCP?

MCP is the underlying connection standard. Apps SDK provides tools for building apps in ChatGPT. UI is optional and can use the MCP Apps standard.

Can one MCP server work with ChatGPT, Claude and Cursor?

Yes, provided each client supports the features you use. The shared server can be reused, but authentication, tool behaviour and any interface need testing in each target client.

Does a custom Claude connector appear in the directory?

Adding a custom connector by URL gives selected users a connection to your service. It does not automatically create a public listing in the Claude connectors directory.

Will an MCP server make ChatGPT recommend my business?

An MCP integration enables connected users to use your tools. Directory publication and visibility in general AI answers are separate outcomes. Neither recommendations nor customer acquisition follow automatically from building a server.

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