n8n vs Make.com for AI Agents

n8n is open source and free to self-host. That single fact defines everything about it. If you are comfortable spinning up a VPS, installing n8n, and maintaining it yourself, you get a powerful workflow automation tool for the cost of your server — typically $5 to $20 per month on a basic DigitalOcean or Hetzner instance. At any meaningful workflow volume that is dramatically cheaper than Make's paid plans. For cost-conscious builders running high-volume AI agent workflows, self-hosted n8n is the most economical option available.

The developer experience in n8n is genuinely excellent. The Code node lets you drop into JavaScript or Python mid-workflow, which means you can do data transformations and custom logic that would require workarounds in Make. If you are technical enough to write a few lines of code, n8n gives you an escape hatch that Make simply does not have. The community is large, active, and produces a constant stream of workflow templates.

Where n8n falls short is the self-hosting overhead. It is not difficult to set up but it is a real barrier for non-technical users and agencies managing client work. If your VPS goes down, your workflows stop. If a new version breaks something, you are the one who fixes it. For agencies building automation for clients who expect reliability guarantees, that managed infrastructure responsibility is a genuine operational burden.

n8n does offer a cloud version starting around $20/month which removes the self-hosting concern. At that price point the comparison with Make's paid plans becomes closer. The Code node flexibility and the open source ethos are still advantages, but the cost argument weakens significantly unless you are running at high volume where Make's per-operation pricing starts to add up.

Make.com runs in the cloud, is maintained by a team, and has an SLA. For agencies building automation for clients who expect things to just work, that managed infrastructure is worth paying for. You do not need to think about server maintenance, version upgrades, or uptime monitoring. Make handles it.

The scenario builder is polished in a way that n8n's interface, while functional, is not quite. The onboarding experience is better, the documentation is more comprehensive for beginners, and the error handling UI makes debugging workflows more accessible to non-technical users. If you are introducing automation to a team for the first time, Make will get them productive faster.

Make's app library — over 1,000 integrations — covers the vast majority of tools that AI agent builders actually use. The gaps versus n8n's custom code flexibility matter less in practice than they sound in theory, because most agent workflows are connecting the same set of tools: OpenAI, Anthropic, Google Sheets, webhooks, Slack, Airtable, and CRM systems that are all well-supported on Make.

The pricing model does become a consideration at scale. Make charges per operation and the costs can grow quickly for high-frequency workflows. Self-hosted n8n at scale is significantly cheaper. This is the core trade-off: Make's convenience costs money, n8n's savings cost operational attention.