MCP · Model Context Protocol
Model Context Protocol
What is MCP?
- A standard way to connect AI to external tools and data
- An open protocol, “like USB-C”
- Simplifies tool connections
In the past, every time you connected an internal system to AI, you had to write new custom integration code. Connect 3 AI tools to 5 business systems and you get 15 integrations, all of which needed rework whenever either side changed. MCP is a structure that turns this multiplication into addition. Once you build an MCP server on the business-system side, any AI that supports the protocol connects the same way. For practitioners, the difference is that the cost of adding one more tool stays constant.
An MCP server gives AI three main things: 'tools' that trigger real actions, 'resources' that serve as read-only data, and 'prompts' that bundle repeatable tasks. It connects in one of two ways: locally, running on an employee’s PC, or remotely, hosted on an in-house server or in the cloud and shared by many people. It is easy to confuse with RAG: RAG stops once it has retrieved documents for the AI to read, while MCP goes on to take action, such as looking up, creating, and editing. Nor does it replace your existing internal APIs. Many companies start by putting a thin MCP server in front of their API.
Adoption comes with conditions. The system you want to connect needs a live API or database access path, and your internal accounts and permissions need to be reasonably well organized. Data locked in paper approvals or personal spreadsheets can’t be pulled in, even with MCP. That is why a first project usually starts with read-heavy tasks such as document search or schedule lookup, then expands to write actions that require approval.
The most common mistake in practice is assuming that adding MCP also takes care of security. MCP is only a connection protocol, not a permissions tool, so the permissions of the account attached to the server become the AI’s permissions. If a database is connected with an admin account, a single misread instruction could wipe data. Installing public MCP servers of unknown origin is also risky: there are reported cases of sentences hidden in tool descriptions steering the model. It is safer to start with read-only accounts and open access one folder at a time.
John KimInstructor John Kim, author of "B2B Marketing Design" and CEO of Nanum Consulting
Seungtae ParkAX instructor who teaches by building AI business development and marketing automation himselfAnthropic released it in 2024 as an open standard for connecting AI models to external tools and data. Many AI tools and platforms have since adopted it, and it has spread quickly.
Consider a hypothetical case. Company A, a Korean industrial parts manufacturer (320 employees, KRW 118 billion (≈ US$88,283,700) in annual revenue), took an average of 2.5 days to answer quote inquiries from overseas distributors. Price lists sat in the ERP, drawings on a shared drive, and past quotes in individual reps’ mailboxes. The sales support and information strategy teams were given eight weeks to connect an in-house AI assistant through MCP.
- Kim, a manager on the sales support team, went through 142 quote inquiries from the past 3 weeks and found that 68% of reply delays were wait time caused by not knowing where to find the latest price list.
- When Manager Park on the information strategy team set up the MCP server for ERP lookups, they connected it with a read-only account. Their rule: "Give it edit permissions and an accident is only a matter of time."
- They did not open the shared drive wholesale. They exposed only three folders, such as 'Product Drawings/Current,' because the same drive also held HR and payroll folders.
- During the two-week pilot, the AI pulled prices for discontinued items 11 times. The team fixed it by adding 'check the discontinued-status field first' to the tool description.
- Eight weeks later, the average quote reply time had fallen from 2.5 days to 4 hours, and the time the sales support team spent searching for materials dropped from 12 hours a week to 3.