What is an MCP server and how does it work?

What is an MCP server?

An MCP server is a bridge through which an AI program, such as ChatGPT or Claude, can securely access external data and tools. It "explains" to the AI program what information can be obtained and what actions can be performed, and then executes them according to set permissions.

MCP stands for Model Context Protocol. It is an open standard that describes how AI programs should communicate with external data sources. Simply put, it's a common "language" understood by both the AI program and your system's connector. Because of it, there's no need to create a completely separate integration for each AI program.

On its own, an AI model only knows what it was trained on and what you provide in the conversation. It doesn't see your customer list, unpaid invoices, or warehouse balances. An MCP server fills this gap: it provides controlled access to specific data needed for an answer.

For business, this means that employees can ask a question in natural language and get an answer from real company data, instead of searching for information in several different systems.

How does an MCP server work?

From the user's side, everything looks like a regular conversation. However, behind it, a clear sequence of actions takes place:

1. The user asks a question to ChatGPT or Claude.
2. The AI program selects the appropriate MCP server tool, for example, "find unpaid invoices".
3. The MCP server contacts the connected system based on provided permissions.
4. The system returns the necessary data.
5. The AI program processes them and provides a user-understandable answer.

Each MCP server tool has a clear description: what it does, what data it needs, and what it returns. Based on these descriptions, the AI program understands which tool to use for a specific question.

How is an MCP server different from an API?

API and MCP are often mentioned together, so the question arises whether they are the same thing. The short answer is no, but they are closely related.

MCP and API are not direct competitors. An MCP server often uses your existing CRM, ERP, or accounting system APIs and presents them to the AI program in a uniform, understandable format.

How is an MCP server used in business?

The greatest benefit arises where employees daily search for information in different systems. A few practical examples:

CRM

"Which customers bought less this month than last?" Needs customer and their purchase history data. The sales manager immediately sees who is worth contacting, without manual report comparison.

Accounting

"How many unpaid invoices do we have?" Needs invoices and payment statuses. The financier gets the amount and list in seconds, without opening the accounting software.

ERP

"Which orders are delayed?" Needs orders, deadlines, and statuses. The logistics team notices problems faster and can inform customers.

Warehouse

"Which products have a balance of less than 10 units?" Needs stock balance data. The purchasing specialist orders missing goods in time.

Documents

"Find the latest contract with Baltic Trade." Needs access to the document repository. The employee saves time that would have been spent browsing folders.

Can one MCP server connect multiple systems?

Yes. A custom MCP server can provide tools for working with several systems at once if they are technically integrable. Then the AI program can combine information from CRM, accounting, and other sources in one conversation:

In this example, the first answer is based on CRM data, the second on accounting, and the third step prepares actions in the CRM system. The user doesn't need to know where each answer comes from.

Can an MCP server perform actions?

An MCP server can provide tools not only for reading data but also for performing allowed actions. For example:

• Creating a task in CRM.
• Updating order status.
• Preparing a report.
• Document search.
• Preparing a reminder.

Action possibilities depend on the system integration and granted permissions. For more sensitive actions, additional confirmation can be implemented – the AI prepares the action, and the user reviews and confirms it.

Is it safe to use an MCP server?

Security depends on the architecture and configuration of the specific solution. When creating an MCP server, it's worth paying attention to these areas:

• Authentication – only verified users can connect to the bridge.
• Access rights – each tool only accesses the data it needs.
• User roles – manager, employee, or client see different information.
• Data minimization – only what is needed for the answer is passed to the AI program.
• Action confirmation – more sensitive changes are made only after user confirmation.
• Data transfer conditions – it is important to evaluate how the used AI service handles the data passed to it.

When is it worth creating a custom MCP server?

Custom integration usually makes sense when:

• The company uses multiple business systems.
• Employees are constantly searching for information.
• There's a need to combine data from several systems.
• Different access levels are desired for teams.
• There's a desire to perform specific business actions via AI.

However, not every need requires a custom MCP server. Some systems already have their own connectors, and sometimes a simpler integration is enough. Therefore, it's first worth evaluating which systems you use and what information is needed most often.

Summary

An MCP server is a standardized bridge that allows ChatGPT or Claude to access your business system data and, when allowed, perform actions. It doesn't replace existing systems and APIs, but makes them accessible through a simple conversation.

If you're considering how to apply this in your company, read more on our page Custom MCP Server Development.