What is MCP (Model Context Protocol) and how can a business use it?
MCP is the open standard that connects AI assistants to a company's applications and data. Here is how it works, where it adds value and what to consider for security.
AI assistants such as Claude, ChatGPT and Gemini are increasingly capable, but by default they have no access to company data: the CRM, the ERP, internal documents or the database. Until recently, every integration had to be built separately, for each assistant. The Model Context Protocol (MCP) solves exactly this problem.
What MCP is
MCP is an open standard that defines how AI applications connect to external tools and data sources. It was introduced by Anthropic in November 2024 and, in December 2025, was transferred to the Agentic AI Foundation, a foundation under the Linux Foundation. Today, MCP is supported by the major AI platforms and tools.
The simplest analogy: MCP is to AI what USB-C is to devices. One standard interface that works with many different “consumers”.
How it works
The architecture has three components:
- The host application — the AI assistant the user works with (for example Claude, ChatGPT or a custom agent).
- The MCP client — the component inside the host that speaks the protocol.
- The MCP server — the service that exposes an application’s data and functions in a controlled way.
An MCP server can offer three kinds of capabilities:
- Tools — actions the AI can perform: “create a quote”, “check stock”, “book a meeting”.
- Resources — data the AI can read: customer records, documents, reports.
- Prompts — predefined templates for common tasks.
Communication happens locally or over HTTP, and for remotely accessible servers the standard specifies authentication via OAuth.
Why it matters for a business
One integration, many assistants. An MCP server built for your CRM works with any compatible AI assistant. If your team switches providers, the integration still works.
Controlled access. The server decides exactly which data and actions are available, per user. The AI does not get unrestricted access to your database — only to the functions you explicitly expose.
Less copy-paste. Your team can work with company data directly from their AI assistant: “What are the 10 largest overdue orders this month?” or “Prepare a quote for client X based on their last three orders.”
Concrete examples
- Sales: the assistant looks up the customer history in the CRM, checks prices in the ERP and drafts a quote.
- Operations: an agent checks stock levels daily and flags products below the minimum threshold.
- Finance: incoming invoices are captured, validated and entered into the accounting system automatically, with human approval for exceptions.
- Support: agents get answers from internal documentation and order status without searching across several applications.
Security considerations
MCP provides the technical framework, but security depends on the implementation. Our recommendations:
- Least privilege — expose only the functions that are strictly needed, with separate permissions per role.
- Human approval for critical actions — payments, deletions or messages to customers are never executed without confirmation.
- Audit log — every tool call is recorded: who, what, when.
- Prompt-injection protection — content from external sources (emails, documents) is treated as data, not as instructions.
- Data control — choose providers and configurations that do not train on your data and, if needed, process data within the EU.
How to get started
We recommend a pilot project: pick one repetitive process with measurable impact and build an MCP server for that process only. Within a few weeks you will have real data on time saved and on how your team uses the new tool.
If you would like to assess together where MCP would deliver the highest return in your company, book a call or learn more about our AI & automation services.