What Is an MCP Server? The Plug That Connects AI to Your Business
AI assistants have become remarkably good at writing, summarizing, and reasoning. Ask one to draft a customer email and it will do a respectable job. Now ask how many units of a part are on hand in your Cleveland warehouse. Or ask which jobs are running late this week. It hits a wall. The model is smart, but it is cut off from the systems where your business lives.
That gap is exactly what the Model Context Protocol, better known as MCP, was built to close. Maybe you have heard the term “MCP server” in a vendor briefing or a LinkedIn post. If you wondered what it means for your company, this article is for you.
MCP in plain language
MCP is an open standard for connecting AI applications to outside systems. Those systems include files, databases, business applications, and web services. The official documentation describes it as a USB-C port for AI applications. The comparison is a good one. Before USB-C, every device needed its own cable. Now one connector works almost everywhere.
Before MCP, every AI tool needed a custom integration for every system it wanted to reach. One connector for the CRM, another for the file share, a third for the ticketing system. Each one had to be rebuilt for every new AI product. MCP replaces that tangle with one common language. Build a connector once, and any AI application that speaks MCP can use it.
What an MCP server actually does
An MCP server sits in front of a system and makes it available to AI in a standard way. Think of it as a translator and a gatekeeper rolled into one. The AI application, called the host, connects to one or more MCP servers. Each server tells the AI what it can offer.
According to the MCP specification, a server can expose three kinds of capabilities:
- Tools are actions the AI can take, such as looking up an order or updating a record.
- Resources are read-only information the AI can use for context, such as documents or product specifications.
- Prompts are prebuilt instruction templates that guide AI through a common task, such as drafting a quote follow-up.
When an AI assistant connects to an MCP server, it first asks what the server can do. The server answers with a list of its tools. Each tool has a plain-language description and a defined set of inputs. The AI then decides which tool fits the user’s request and calls it.
MCP servers can run locally on a user’s computer or remotely as a hosted service. A remote server, often hosted in a cloud platform such as Azure, can serve many users at once.
Why everyone is talking about it
Anthropic introduced MCP and released it as open source in November 2024. Adoption since then has been fast. In December 2025, MCP was donated to the Agentic AI Foundation. This new fund under the Linux Foundation was co-founded by Anthropic, Block and OpenAI. Microsoft, Google, and Amazon Web Services are among its supporting members. At that point, the Linux Foundation reported more than 10,000 published MCP servers. The protocol had been adopted by Microsoft Copilot, Visual Studio Code, ChatGPT, Gemini, Claude, and Cursor.
Moving the standard to a neutral foundation matters for business buyers. It means MCP is not tied to one AI vendor. An investment in MCP today should keep working as your AI tools change. Standard network protocols have rewarded that kind of investment for decades.
Microsoft is all in. MCP is supported across GitHub Copilot, Visual Studio Code and Azure. Microsoft also publishes its own MCP servers, including one that serves official Microsoft Learn documentation. It has published guidance on securing MCP servers with Microsoft Entra ID. That way, every request is tied to a real, signed-in user.
What MCP could look like on the shop floor and in the warehouse
For manufacturers and distributors, the real promise of MCP is an AI assistant that works with live business data. No more guessing. Here are a few examples of what that can look like:
- A customer service rep asks Copilot whether an order will ship on time. The assistant checks the order, the job status and inventory before answering.
- A purchasing manager asks which open purchase orders are past their promised date. The answer comes back with vendor contacts ready for follow-up.
- A plant manager asks for a summary of yesterday’s scrap by work center, pulled straight from production data.
- A sales rep preparing for a meeting asks for order history, open quotes, and recent support cases in one view.
None of this requires the user to know which system holds the data or how to run a report. The MCP servers manage the connection, and the AI manages the conversation. More ERP, CRM and business software vendors are adding MCP support. Companies are also building their own MCP servers for internal systems. As that happens, these scenarios become much easier to deliver.
Security is not optional
Connecting AI to business systems is powerful. That is exactly why it must be done carefully. An MCP server is software that can read your data and, in many cases, act on it. Treat it with the same care you would give any application that touches your ERP.
A few principles go a long way:
- Use servers from trusted sources only. Review what each one can access before you connect it.
- Tie every connection to a real identity. With Microsoft Entra ID, the AI acts with the permissions of the signed-in user, and never more.
- Start with read-only access. Add write actions only where there is a clear business case and an approval step.
- Keep human approval in the loop for actions that send, change, or delete anything. The MCP specification itself encourages approval prompts and activity logs.
- Watch for prompt injection. This is where hidden instructions in an email, document or web page try to trick the AI. Limiting what each server can do is the best defense.
- Log and monitor tool activity the same way you monitor other privileged access.
Many companies work under CMMC, ITAR or other compliance frameworks. For them, MCP deployments belong inside the same governance program as the rest of the environment.
How to get started
You do not need a massive AI program to begin. Start with one high-value, low-risk use case, such as read-only order status or inventory lookup. Pilot it with a small group. Use that pilot to work out identity, permissions, logging, and user training. Then expand to more systems and more people once the foundation is proven.
Hosting MCP servers in your own Azure environment keeps your data inside a tenant you control. It also sits alongside the security, and monitoring tools you already use. Best of all, it gives you one consistent way to connect AI to Epicor, Microsoft 365, Dynamics 365, and other systems.
The bottom line
MCP servers are quickly becoming the standard way AI reaches into real business systems. They turn AI assistants from clever writers into useful coworkers. Those coworkers can look things up, pull reports, and help get work done. The companies that benefit most will adopt MCP thoughtfully. That means strong identity, clear permissions, and a focus on real business problems.
2W Tech brings ERP expertise as an Epicor Platinum Elite partner. We add cloud expertise as a Microsoft Tier 1 Cloud Solutions Provider. Our security and managed services experience help you put AI to work safely. Wondering where MCP and AI agents fit in your business? We would be glad to help you find the right first step.
Ready to talk about AI and MCP for your business? Reach out.
2W Tech. Every Solution. One Partner.
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