MCP is useful, but not every integration needs it.
Single Application, Single Integration
If one application needs to call one internal API, defining a tool directly in your code is simpler than running a separate server.
Latency-Critical Paths
An extra process or network hop adds latency. For tight loops, in-process tools may be better.
Fixed Workflows
If the steps are always the same, ordinary code calling APIs is more predictable than giving a model tools to choose between.
Highly Sensitive Operations
Some actions — payments, production deletions, account changes — may be better left out of AI tool access entirely, or exposed only through tightly controlled, purpose-built interfaces.
Heavy Data Processing
Streaming gigabytes through tool results isn't practical. Process data in the back end and return summaries.
When MCP Shines
- Many AI applications need the same integration.
- A product wants to let customers connect their own AI tools.
- A host needs many integrations maintained by different teams.
Choose the approach that keeps the system simple, secure and maintainable.