n8n

n8n pairs a visual canvas with real code. You drag nodes to shape a workflow, then drop into JavaScript or Python where the visual metaphor stops paying off, which removes the usual choice between a no-code tool you outgrow and a script nobody else can maintain.

Workflows can run as multi-step agents that use your own data, models and tools. Providers are interchangeable, so moving between OpenAI, Anthropic, Google and open source models does not mean redrawing the architecture around them.

These are the capabilities that carry a workflow from prototype to something people depend on.

• Code inside the canvas: JavaScript, Python and npm packages sit next to the visual nodes.
• Human approvals: a flow pauses for a person before an agent takes a consequential step.
• Observability: runs are traceable across multi-step logic, which is what you want when an agent misbehaves overnight.
• Access control: role-based permissions and audit trails support sensitive data on self-hosted deployments.
• Existing building blocks: more than 1500 integrations and 9000 workflow templates cover the connective work.

An install script starts n8n with Docker, or you can run the container by hand and open the editor on port 5678, and a hosted cloud exists for anyone who prefers not to operate it. The source is always visible under a fair-code sustainable use license, with a separate enterprise license for additional features, and you can write your own nodes.