n8n vs Zapier vs Make for AI agents in 2026
Ayo Adeniran · Oct 15, 2026 · 5 min read
All three started as ways to connect apps without writing code. All three now sell AI agents. And all three will happily run an agent that reads an email, looks something up and replies.
Where they differ is in how they charge for an agent's many small steps, how a person steps in, and how they connect to the AI tools your team already uses. Those differences matter more for agents than they ever did for "new row, send Slack message."
Pricing and how usage is counted
| n8n | Zapier | Make | |
|---|---|---|---|
| Free | Community Edition, self-hosted | 100 tasks a month | 1,000 credits a month |
| Entry paid plan | Starter: €20 a month billed annually, 2,500 executions | Pro: from $19.99 a month billed annually, 750 tasks | Core: $9 for 10,000 credits a month |
| Next plan | Pro: €50 a month billed annually, 10,000 executions | Team: from $69 a month billed annually, 2,000 tasks | Teams: $29 a month, from 10,000 credits |
| What counts | One execution per workflow run, however many steps | One task per completed action; triggers and built-ins like Formatter and Delay don't count | Most module actions use 1 credit; some AI features use more |
| AI agents | AI Agent node in workflows | Zapier Agents, billed in activities: 400 a month free, 1,500 on Pro | Make AI Agents on every paid plan |
The counting model is the part to read twice. Agents take many steps. n8n counts a run of the whole workflow as one execution: "It doesn't matter how many steps are in the workflow or how much data it processes." Zapier counts each action that completes. Make counts module actions in credits. A twelve-step agent workflow that runs 1,000 times is 1,000 executions on n8n, and many thousands of tasks or credits on the other two, depending on which steps are actions.
Zapier Agents have their own meter: activities rather than tasks, with Pro at 1,500 activities a month for about $33.33 a month billed annually.
How a person steps in
Agents that act need a way for a human to say yes or no before something irreversible happens.
n8n has human-in-the-loop for AI tools. Mark a tool as needing review and, when the agent wants it, the workflow pauses and sends an approval request to Slack, Discord, Telegram, Microsoft Teams, Gmail, Outlook, WhatsApp, Google Chat or n8n's chat. Approve and the tool runs with the agent's input; deny and the agent is told. For longer pauses, n8n's Wait node offloads the execution's data to the database when a wait exceeds 65 seconds and reloads it when the wait ends.
Zapier has Human in the Loop, a premium built-in tool. Its Request Approval action pauses a Zap and asks reviewers to approve, decline or edit data, with notifications by email or Slack. You choose what happens on a timeout: skip and continue, or end the run, with optional reminders.
Make builds AI agents into scenarios and lets you ground them by uploading files, without setting up retrieval yourself.
Connecting to Claude and ChatGPT
MCP is now how assistants reach your tools.
- n8n's MCP Server Trigger makes n8n act as an MCP server, exposing n8n tools and workflows at a URL that MCP clients call. It supports SSE and streamable HTTP, with no authentication, bearer auth or header auth.
- Zapier MCP is included on every plan and gives AI tools access to thousands of apps without custom API work.
Which one fits
n8n suits technical teams that want to self-host, or run agents with many steps per run, where per-execution pricing is kind to long workflows.
Zapier suits teams that need the widest set of app integrations, 9,000+ of them, and a gentle start, and are comfortable paying per task.
Make suits teams that want a visual builder at a low entry price, more than 1,000 standard app integrations, and AI agents included on paid plans.
When the agent is really a process
There is a class of work none of these were first designed around: work that can take days, must not lose its place, and has to show afterwards exactly what happened. A refund that waits two days for finance. A supplier change that ripples through open orders. That is what Momor Workflows is built for.
Every step written down before it counts. A run records each step, model reply, tool call and answer in order. After a restart it continues from the first step that did not finish, and finished steps never run twice.
Waits that last as long as they need to. A Wait step asks a person a question and the run keeps its place until they answer, holding no worker. Time spent waiting does not count against the run's working time.
Approval before a tool acts. A tool from a connected MCP server can be marked as needing approval. The call waits until the run's owner allows it, or refuses with a reason the run is told.
The right model for each step, with failover. Every model call goes through Momor Gateway, so a cheap model can judge and a stronger one can write, and a call moves to another provider when one fails.
Versions that hold. Each saved version is named by its content hash, and a run finishes on the version it started with.
MCP in both directions. Connected MCP servers' tools become steps, signed in through OAuth, as one account for the organization or as each member's own. And an organization's chosen workflows are served as MCP tools to claude.ai, ChatGPT and other clients, which sign the person in, so each run belongs to that person.
What to weigh, honestly:
- Fewer starters. A run starts from an API call, Momor's Chat or an MCP client. There is no schedule, email or webhook trigger yet; start those runs from your own scheduler or webhook handler.
- No app catalog. Momor connects to your systems through MCP servers rather than thousands of prebuilt integrations, and connecting a server is done with Momor's help for now.
- Priced by agreement, around the workflows you run, how often and the models they call.
If your agents mostly glue apps together, pick from n8n, Zapier and Make by the table above. If they carry decisions that wait on people and must be explained later, read the Workflows quickstart or talk to us.