n8n

What is n8n?

n8n is a workflow automation tool that connects apps, APIs and AI models into visual, node-based workflows. What sets it apart from simpler automation tools is how far it lets you go: alongside standard triggers and actions, n8n has dedicated AI agent nodes that let a workflow call a large language model, hand it access to tools like web search, a database or your own APIs, and let the model decide what to do next within the flow you’ve built.

It’s open source and can be self-hosted, which appeals to technical teams that want full control over their data, their AI provider costs and how their automations run, rather than depending entirely on a hosted service.

Key features

• AI agent nodes. Build agents that reason over a task, call tools and produce a result, instead of following a rigid fixed sequence.
• Multiple LLM providers. Connect different AI models rather than being tied to one company’s API.
• Visual workflow builder. Drag and connect nodes to define triggers, logic and actions, with the option to drop into custom code when needed.
• Wide app connections. Trigger workflows from, or send results to, a large range of apps and services via built-in or custom nodes.
• Self-hosting. Run n8n on your own infrastructure for control over data, cost and uptime.
• Error handling and retries. Build in logic for what happens when a step or an AI call fails, which matters more once agents are making decisions mid-workflow.

How to get started

1. Sign up for n8n cloud, or self-host it on your own server.
2. Create a new workflow and add a trigger, such as a webhook, schedule or app event.
3. Add an AI agent node, connect it to an LLM provider, and define which tools it can use.
4. Test the workflow with sample input and review each step’s output.
5. Activate the workflow and monitor its executions for errors or unexpected AI behaviour.

Who n8n is for

Technical teams and developers who want to build AI agents that actually do things — query a database, call an internal API, update a record — rather than only answer questions in a chat window. It also suits businesses that want to self-host their automation for cost or data-control reasons, and anyone whose automation needs have outgrown simple no-code triggers.

Tips for building AI agents in n8n

• Give the agent a narrow, well-defined set of tools rather than access to everything; a focused agent is easier to debug and more reliable.
• Use the cron expression generator to get scheduling syntax right on the first try for time-based triggers.
• Validate the JSON your AI nodes pass between steps with the JSON formatter when a workflow isn’t behaving as expected.
• Generate unique identifiers for tracking workflow runs or records with the UUID generator when your own data model needs them.
• Log intermediate outputs while building, so you can see exactly what the agent decided at each step before trusting it to run unattended.

n8n vs alternatives

Make offers a similarly visual builder with AI/LLM modules, but leans slightly more toward business users than developers, with less flexibility for custom code. Zapier is the simplest of the three to start with and has the largest app library, including its own AI Agents feature, but gives up some of the control n8n offers over agent reasoning and hosting. Notion AI isn’t an automation platform at all — it’s useful for writing and search inside Notion, while n8n would be what actually moves data in and out of it. Manus runs one-off autonomous tasks on demand, whereas n8n is built for repeatable, triggered workflows you define once and reuse.

Is n8n worth it?

For teams that need AI agents wired into real systems — not just chatting, but querying, updating and acting — n8n’s combination of AI agent nodes, broad app support and self-hosting makes it one of the more capable options available. It asks more of you upfront than a simple no-code tool, and self-hosting adds real maintenance work, but that investment pays off once you’re running AI-driven workflows that need to be reliable and cost-controlled. Simpler, occasional automations may not need this much power.

Compare it with other automation platforms in the AI tools catalog.