What Is the Model Context Protocol (MCP)? Simple Definition
Simple definition of the Model Context Protocol (MCP): how it works, what it does for enterprises, and real-world examples. Connect your IT landscape to AI with UrbaHive.
Frédéric Le Bris
CEO & Co-founder
You have heard about the Model Context Protocol but are not quite sure what it is. You are not alone. This technical standard has attracted significant attention since Anthropic launched it, yet most explanations are either too abstract or too deeply technical. This article gives you a clear definition, illustrated with practical examples from the business world.
Definition: The Model Context Protocol in One Sentence
The Model Context Protocol (MCP) is an open standard that allows an AI assistant to connect to external data sources — databases, business tools, IT architecture maps — so it can answer questions about your actual context rather than generic generalities.
In other words: without MCP, an AI assistant like Claude has no idea which applications make up your IT landscape, how they are connected, or which processes they support. With MCP, it can answer precise questions about your organisation.
Why AI Assistants Need Context
A large language model (LLM) is trained on billions of documents. It performs very well at writing, summarising, and reasoning. But it knows nothing specific about your organisation: not your application portfolio, not your team structure, not your particular regulatory constraints.
To be useful on internal topics, the AI needs you to provide that context. Until recently, this meant copying and pasting text into the conversation — a manual, unreliable, and hard-to-scale approach. MCP automates and structures this context transfer.
How MCP Works: The Translator Analogy
Picture an external expert (the AI) who knows nothing about your company. To answer your questions, they need an internal contact who feeds them the relevant information in real time. MCP plays that role — as a structured, always-available internal contact.
More technically, MCP rests on a three-part architecture:
The client — this is the AI application you use (Claude Desktop, claude.ai, etc.). It sends queries to the MCP server.
The MCP server — this is the component provided by a data supplier (UrbaHive, for example). It holds your data and responds to client queries according to defined rules.
The context — this is the server's response, passed to the model to enrich its answer. The model integrates this data into its reasoning.
One important point: the AI model does not store your data. It receives it within a session, uses it to formulate a response, and that is the end of it.
For a deeper look at how MCP works and its enterprise use cases, see our full guide Model Context Protocol: Connecting AI to Your IT Systems.
Concrete Examples of What MCP Makes Possible
Here are questions a CIO or IT architect can ask Claude once MCP is configured with UrbaHive:
- "Which applications depend on the production SAP server?"
- "Summarise my application landscape in five points."
- "Which business processes run through Salesforce?"
- "Are there any internet-facing applications not linked to a business process?"
- "Which applications have been modified in the past three months?"
In each case, Claude queries the UrbaHive MCP server, retrieves data from your IT map, and formulates an answer grounded in your reality — not a generic hypothesis.
MCP and Security: What You Need to Know
The first question CIOs and CISOs ask is: "Does my data go to Anthropic?"
The answer depends on the implementation. In UrbaHive's case, the MCP server works as follows:
- It provides only the data strictly needed for the query (not a full database export).
- It operates in read-only mode: the AI cannot create, modify, or delete anything in UrbaHive.
- Every call is logged in UrbaHive's audit trail.
- The server is hosted in Europe, GDPR-compliant.
- Access is controlled by a PAT token that can be revoked at any time.
These safeguards are designed for mid-market environments that must meet NIS2 or DORA requirements. For more on compliance, read NIS2 for SMEs: IT Mapping and Compliance.
MCP vs. RAG vs. Fine-Tuning: What's the Difference?
All three approaches allow you to contextualise an LLM, but they serve different purposes:
| Approach | Principle | Best for |
|---|---|---|
| Fine-tuning | Retrain the model on your data | Permanently adapting style or domain knowledge |
| RAG (Retrieval-Augmented Generation) | Retrieve relevant text documents before generating | Querying document repositories (PDFs, notes, emails) |
| MCP | Connect the model to structured data APIs in real time | Querying live references (IT systems, CRM, ERP, architecture maps) |
For IT mapping, MCP is the right approach: your data is structured, changes regularly, and you need up-to-date answers — not a synthesis of static documents.
Who Created the Model Context Protocol?
MCP was designed and published by Anthropic, the company behind the Claude assistant, in November 2024. It has since been opened to the community as a public specification, and other vendors are beginning to implement it in their products.
UrbaHive is among the first IT mapping platforms to have integrated a native MCP server, allowing IT teams to connect Claude to their enterprise architecture repository. See the UrbaHive Connectors page.
Conclusion
The Model Context Protocol is not just another buzzword. It is an infrastructure building block that concretely changes what AI can do for your IT team: moving from generic answers to analyses grounded in your actual IT reality.
To go further: learn how to configure MCP in minutes in our tutorial Connect Claude to Your IT Map with MCP, or explore all the mapping features in our IT architecture guide for mid-market organisations.
Ready to try it? Create your free account at app.urbahive.com/signup.
FAQ — What Is MCP?
What does MCP stand for?
MCP stands for Model Context Protocol. It is the technical standard that defines how an AI assistant communicates with external data sources in a structured, secure way.
Is MCP only for developers?
No. Setting up an MCP server requires a few technical steps (generating a token, editing a configuration file), but day-to-day use is fully accessible to non-developers. Once configured, you interact with your IT landscape in plain language.
Does MCP only work with Claude?
MCP was created by Anthropic and is natively integrated into Claude products. Other vendors are beginning to support it, but Claude (Desktop, claude.ai, Claude Code) remains today the most complete environment in which to exploit its full potential.
Can MCP be used for free?
The MCP protocol is an open, free standard. Access to UrbaHive's MCP server is included in paid plans (starting with Starter at €29/month). A Free plan is available to explore the platform.
Does MCP replace a classic API integration?
No — they are complementary approaches. A classic API integration automates communication between two systems. MCP creates a channel between a data system and an AI assistant, so that a human user can interact with that data in natural language.