Model Context Protocol (MCP): definition and framing
Definition
The Model Context Protocol (MCP) is an open standard through which a language model accesses external tools, data sources and services. Instead of building a separate interface for every connection, the model talks to so-called MCP servers over one common protocol. Files, databases or line-of-business applications can then be coupled to an AI solution in an interchangeable way.
Why the Term Matters
Anyone using AI in operations almost always connects it to existing systems. Without a standard, a web of one-off connections appears that is expensive to maintain. MCP reduces that coupling to a shared format. For neutral consulting the term matters because choosing open standards preserves later vendor interchangeability and limits lock-in before budget flows into hard-wired integrations.
When It Is Relevant
- An AI solution must access several internal data sources.
- Vendors and models should stay interchangeable rather than hard-wired.
- Multiple applications should be reachable through one uniform connection.
- A proof of concept should later move cleanly into operations.
When Not
When only a single stable interface needs connecting, a direct call is often leaner than an extra protocol. And with strictly regulated data that must not reach the model at all, MCP does not solve the real problem; the question of data release comes before any technical connection.
Industries That Use It
- Machinery and plant engineering: make ERP, PLM and document storage reachable through one shared connection instead of silos.
- Logistics and freight: merge shipment, warehouse and route data from separate systems for assistant functions.
- Tax and audit firms: couple specialist applications to a model in a controlled, logged way instead of copying data by hand.
- Utilities: connect grid, billing and customer systems through interchangeable servers.
Typical Use Cases
- An internal assistant reads from a knowledge base and a ticket system via MCP.
- An analysis tool accesses a database without storing credentials in the model.
- An approval chain is connected so the model only prepares cases, never triggers them.
- Several models are tested against the same MCP server to compare vendors.
- A legacy application becomes accessible through a thin server instead of a rebuild.
Decision Guide
| Signal | MCP fits | Alternative |
|---|---|---|
| Several sources, one assistant | uniform connection via MCP | one-off integrations get expensive fast |
| Vendor should stay swappable | open standard reduces lock-in | proprietary interface binds you |
| Only one stable interface | rather not | a direct call is enough |
| Data must not reach the model | clarify release first | opening access wholesale is risky |
Example
A manufacturer wants an internal assistant coupled to ERP, document storage and a ticket system. Instead of three hard-wired integrations, we assess an MCP-based connection where each source is its own server. The model stays swappable and access stays logged. This describes the method, not an asserted client metric.
Service Connection
We plan the connection within AI implementation; whether it is even the right step is clarified first by the AI readiness check or the AI potential analysis.
Sources
This framing describes common architecture practice around open connection standards. The concrete implementation depends on the systems in use and should be reviewed technically case by case.