MCP vs API vs Zapier: when to use each
Use an API when developers need a dependable software contract. Use Zapier when the same trigger should run the same steps every time. Use MCP when an AI assistant needs to choose the steps for a changing task. The simplest test is this: who should decide what happens next?
Key takeaways
- •Who decides the steps sorts all three. Your developer in advance, the person who configured the connector, or the model at runtime.
- •Zapier's determinism is the product, not a shortcoming. Same trigger, same steps, a row in the history.
- •A plain API is right for anything that has to run unattended and identically. The other two sit on top of one.
- •MCP earns its keep on work that varies: analysis, setup, migration, the jobs that cost you twelve browser tabs.
- •Most businesses run all three, plus a fourth option they forget: the automation already inside the platform they pay for.
Who decides the steps?
All three move data between systems and start work in them. That is why they get confused. The difference is not what they can reach, it is where the decision about the order lives.
- •A plain API. You decide, in code, before anything runs. The decision is frozen at deploy.
- •Zapier. You decide once, in a form. The decision is frozen when you switch the Zap on.
- •MCP. The model decides per request, from the list of tools the server hands it.
Everything else follows from that one line: what it costs, how it fails, and who in your company can operate it.
The three, side by side
| Plain REST API | Zapier | MCP server | |
|---|---|---|---|
| Who builds it | your developer | whoever configures the Zap | nobody; the model reads the menu |
| Who decides the sequence | code, written in advance | the person who drew it | the model, per request |
| A task nobody planned for | needs new code | needs a new Zap | attempted from the tools already there |
| Typical failure | an error your code handles | the run stops, with a row in the history | a plausible wrong argument, accepted quietly |
| Repeatability | identical every run | identical every run | varies between runs |
| What you pay for | developer time, then your own hosting | each task the connector runs | model tokens, plus whatever the vendor gates |
| Who can operate it | whoever writes code | whoever can describe a trigger | whoever can describe an outcome |
Read the repeatability row twice. Two of these are machines you can trust at three in the morning. The third is a fast colleague who occasionally misreads the brief.
When a plain API is the right answer
Reach for the API when the work has to run unattended, at volume, or inside your own product. A checkout that provisions access the moment a payment clears, or a nightly reconciliation. Neither should ask a model what to do next.
The API also sits underneath the other two: connectors call it, and an MCP server is a layer over it. Nothing you build here is wasted if you add either later.
Check two things first. How access is scoped, because a key that can do everything is a liability in a job that only reads. And whether the limit is a request quota or a concurrency cap, since a quota takes you dark until the month rolls over and a cap is only a retry.
On AXL that surface is the same API the admin panel calls, every key carries its own rights, and the limit is concurrency rather than a monthly quota. Details on the REST API page.
Curious what the agent version looks like on a real account? See what an AI agent can run end to end on AXL.
When Zapier is the right answer
Zapier's job is to connect two products that will never know about each other. No permission from either vendor, no developer, no server of your own: a catalog of connectors and a form for wiring two of them together. Nothing else in this article does that job.
It is right when three things are true at once: the shape of the work is fixed, the volume is predictable, and both ends are systems you do not control. "When someone books in the scheduling tool, add a row to the finance sheet" is a Zap, and should stay one.
The determinism deserves naming, because it is what people give up when they get excited about agents. A Zap that ran correctly yesterday runs correctly today. When it does not, a row tells you which step failed.
The trade-offs are structural, not a criticism. Billing is metered by the task, so volume changes the arithmetic in a way a flat subscription does not. And a connector reaches only as far as the vendor built it out, so evaluate the connector rather than the logo.
Zapier also publishes MCP endpoints over its own connectors (zapier.com/mcp), which tells you how this is settling: the layers stack rather than replace each other. What an agent gets through a wrapper is still whatever the connector exposes, and for some products that is two actions.
When MCP is the right answer
Use it for work that varies. Analysis nobody built a report for. Setup: a new offer needs a page, a product record, a payment button and a follow-up sequence, each on a different screen. Cleanup: retag four hundred contacts by a rule that only makes sense this quarter.
The test: if the job means twelve browser tabs and ninety minutes and you will never do it in that shape again, it is agent work. If you will do it a thousand times identically, it is not.
The second test is blast radius. An agent that reads is a research assistant; an agent that writes is an operator, and operators earn scope the way new staff do. Start with what you can reverse, and keep money on a human.
If you have not connected one, the mechanics are in our plain-English guide to MCP servers: what the server publishes, how the sign-in works, and what to ask a vendor first.
The fourth option people forget
Before picking any of the three, check whether both ends already live in the same platform. If they do, the connection exists and none of this applies. An automation engine triggers on its own events, like a form submitted or a payment received, and acts on its own records. No third system in the middle, no credentials kept somewhere else, no connector depth to verify.
On AXL that engine is scenarios: 139 node types across events, listeners and actions, and it is where the outbound webhook node lives. Automation built there is deterministic in the same way a Zap is.
The rule: keep automation inside the platform when both ends are inside it, and reach outside only when one is not. People pay a connector service for years to move data between two halves of one product they already own.
Using all three together
In practice they stack into one shape, worth memorising.
- Agent sets it up MCP, once
- Automation runs it Same steps, every customer
- Webhook tells your system Outbound, from a node
- API reads it back Nightly, unattended
Setup varies, so it goes to the agent. Runtime must not, so it does not. You describe the onboarding flow to an agent, which builds the pages, the product and the automation. The automation then runs it the same way for every customer, its webhook posts each one into your billing system, and a nightly job reads the numbers back through the API.
What MCP does not solve
Three limits, and none of them is fixable with a better prompt.
Determinism. The same instruction can take a different route on Tuesday. Fine for a report, wrong for anything that touches money or access.
Cost shape. Tokens scale with the length of the conversation, not with the number of records touched. A long session over twenty contacts can cost more than a connector run over two thousand.
Verification. A deterministic run either completes or shows you the step that failed. An agent can report the parts that worked and never mention step four. Ask for a list of what changed and check it yourself for the first few runs.
An agent is not idempotent. Ask twice and you can get two of the thing. Have it check what already exists before it repeats an instruction.
Where AXL fits
AXL offers all three routes: a remote MCP server over roughly 1,100 admin operations, the REST API used by the admin panel, and inbound and outbound webhooks inside automations.
The agent inherits the signed-in admin's permissions. Twenty-one sensitive operations, including billing writes and role changes, are unavailable. Publishing and sending remain separate actions.
What we do not have is a connector catalog. For two systems that are both somebody else's, Zapier is the right tool and we are not.
The detail lives on three pages: connecting an agent over MCP, the REST API, and webhooks in both directions.
FAQ
Should I cancel Zapier once my tools ship MCP servers?
No. They cover different work. A Zap is a machine you configure once and forget; an agent is somebody you brief each time. Retire a Zap when the job moves inside a single platform, not because a new protocol arrived.
Is MCP just an API with extra steps?
It is a layer over one, and the API underneath still does the work. What MCP adds is a machine-readable menu of operations and an auth handshake, so a model can discover what is available instead of a developer wiring each call in advance.
Can a connector service and an AI agent touch the same account?
Yes. They arrive as different callers with their own credentials and permissions, and both end up at the same API. Give each the narrowest rights that let it do its job.
Which should someone non-technical start with?
Native automation first, if both ends are already in one platform. MCP second, read-only, for questions rather than changes. A connector service when the two systems are genuinely separate. A plain API once you have a developer to own it.
How do I know what each one changed?
Ask that before you switch anything on. On AXL, every webhook call writes its full request and result to the contact's history, success or not, and a site page keeps its last 100 revisions. For an agent, ask it to summarise what it changed and verify the first few yourself.
Three ways in, one account.
MCP for the work that varies, the REST API for the work that must not, and webhooks in both directions. Publishing and sending stay separate, deliberate steps.
- •Calling a scenario via the API: how an outside system starts an automation with one request.
- •Types of actions in a scenario: what the automation can do once it starts.