An API needs a developer to read documentation and write code for each use case. An MCP server publishes a machine-readable description of its own tools, so a model reads that description and makes the call itself. The API still does the work underneath. What changes is who writes the mapping between a request and an endpoint.
The actual difference, in one exchange
An API integration is a set of decisions frozen in code. Someone read the docs, chose the endpoints, wrote the parameter mapping, and shipped it. Ask for something the code did not anticipate and the answer is a ticket.
An MCP server ships a schema instead. Each tool has a name, a description, and typed parameters with their own descriptions. The client hands that list to the model, and the model decides.
Concretely, a GTM request:
Find UK fintechs that raised a Series A in the last 60 days
and are hiring salespeople.Nobody wrote a findUkFintechsThatRaisedAndAreHiring function. The model read the parameters and assembled:
search_signals({
industry: "fintech",
country: "GB",
fundingStage: "series_a",
fundedWithinDays: 60,
hasOpenRole: true,
openRoleTitleContains: "sales"
})Change the question and the mapping changes with it. That is the whole gain: the combinatorial space of questions stopped requiring a matching space of code.
Where each one wins
| API integration | MCP server | Zapier / n8n | |
|---|---|---|---|
| Who writes the mapping | A developer, per use case | The model, at request time | You, once, in a UI |
| Best at | Fixed, high-volume, latency-sensitive paths | Open-ended questions from a person | Repeatable sequences on a trigger |
| Runs unattended | Yes | Not reliably | Yes |
| Handles a new question | Needs a change | Handles it | Needs a new zap |
| Failure mode | Loud. It errors | Quiet. It picks a different tool | Loud. The run fails |
| Determinism | Total | Low | High |
That "quiet" row is the one people underestimate. A broken API integration throws. A model choosing the wrong tool succeeds, returns something plausible, and tells you about it confidently. See why your prospecting agent silently drops results for the version of this that costs you rows.
The rule of thumb
Use an API integration when the same thing must happen the same way every time. Syncing enriched contacts into your CRM on a schedule is an integration. There is no judgement in it, it should run at 3am, and a model in that loop is a liability rather than a feature.
Use an MCP server when a person is asking and the questions vary. Account research, list building, qualification, pre-call prep. These are open-ended by nature, which is precisely the property that makes them expensive to pre-build as endpoints.
Use Zapier or n8n when the work is a fixed sequence that should run without anyone present, and building it in code is not worth it. This overlaps with the first row and the honest distinction is who maintains it rather than what it does.
The mistake in both directions is the same: putting judgement where determinism belongs, or building a hundred endpoints to anticipate questions nobody has asked yet.
What MCP actually standardised
Worth being precise, since the audience for this includes people who will have to implement it.
MCP is a protocol, not a product. Servers expose tools with schemas; clients fetch that list and mediate between a model and those tools. Version identifiers are dates marking the last backwards-incompatible change, and the current revision is 2026-07-28.
That revision moved version negotiation from a session handshake to a per-request declaration: each request states the protocol version it uses and the server accepts or rejects it independently. There is also a server/discover call for asking what a server supports before committing. Clients and servers may each support several versions at once.
For a GTM buyer that detail matters in exactly one place. Client support for the authorization specification lags the protocol revision. As of 25 August 2026 Anthropic documents Claude as supporting the 2025-03-26, 2025-06-18 and 2025-11-25 auth specs, which is behind 2026-07-28. A server built strictly against the newest spec is not guaranteed to authenticate against a client that has not caught up. It is the most common reason a connector works for one person and not another.
What does not change
Data quality. A protocol moves data; it does not improve it. Bad data arriving through a nicer interface is bad data with better prose attached.
Rate limits and cost. The underlying API still meters you. An agent making a hundred calls in an afternoon costs a hundred calls.
Determinism. If you need the same answer every time, you need code, not a model choosing.
Auth. An MCP server has to solve identity, scope and revocation the same way any integration does. It has a specification for it, which is a real improvement over everyone inventing their own, but the work is not gone.
The short version
An API is a contract with a developer. An MCP server is a contract with a model. You want both, for different jobs, and the failure is using either where the other belongs.
If you are choosing a GTM data tool, MCP for sales covers what to evaluate. If you want the plain-English mechanics first, start with what is an MCP server for sales.
Sources
- Model Context Protocol, Versioning. Verified 25 August 2026.
- Anthropic, Building custom connectors. Verified 25 August 2026. Source of the supported authorization specifications.