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Agenta vs n8n

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Both have one
Public API
Both have one
Higher Trust score
Agenta — 91 vs 75 for n8n
Best fit
Agenta: Teams that want shared, scheduled AI agents with approvals and an audit trail · n8n: Technical teams that want to self-host automation with Docker, on-prem or air-gapped
Platforms
Agenta: Web · n8n: Web, Linux

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

AgentaOpen-source shared workspace where teams build agents and automations through chat, with tracing, evals and versioned configs.n8nWorkflow automation with AI-agent nodes that runs on n8n's cloud or self-hosted from GitHub

Side by side

FactAgentan8n
CategoryAI Agents & Autonomous WorkersWorkflow Automation Platforms
Pricing modelFreemiumFreemium
Starts at$29/mo—
Public APIYesYes
Trust score91 / 10075 / 100
PlatformsWeb, APIWeb, Linux, API
CompanyAgentatech UGn8n GmbH
Launched2023—
Last verifiedOct 2, 2026Sep 6, 2026

What our research says

Agenta

Agenta is in transition from an LLMOps tool to an agent workspace, which makes it interesting for teams that want shared agents with tracing and evaluation baked in, and open source underneath. If you only need prompt management and evals, check that the current product still fits that narrower job. The MIT licence and self-hosting option lower the lock-in risk.

Pros

  • MIT-licensed core that can be self-hosted with Docker
  • Free cloud tier plus a $29 Pro plan
  • Human-approval controls for agent actions
  • Tracing, usage and version history for every agent

Cons

  • The product direction changed recently, so older tutorials may not match the interface
  • Free cloud tier limits team members to two and trace retention to one week
  • Runs beyond the included allowance are billed per 10,000

n8n

The automation tool to pick when you want agents and integrations on one canvas and the option to run it on your own hardware; self-hosting from GitHub is the escape hatch Zapier and Make do not offer. Cloud pricing is per execution rather than per task, which rewards long workflows, but the monthly figures hide behind a toggle and the Business tier is a self-hosted licence at a very different price point.

Pros

  • Self-hosted Community Edition on GitHub under a fair-code licence, with 207k stars
  • Agent, model, MCP and RAG nodes alongside 500+ app integrations
  • JavaScript or Python at any step, with a canvas that traces agent reasoning
  • Execution-based cloud billing with unlimited steps per execution
  • Public REST API on all self-hosted editions and on cloud Starter and above

Cons

  • Cloud prices were shown only in euros and only as annual-billing figures
  • Business tier (€667 a month) is self-hosted only, with cloud availability on a waitlist
  • Fair-code licence is not OSI open source, which matters for some corporate policies
  • Forum-only support below Enterprise

Which one fits

Choose Agenta if you need

  • Teams that want shared, scheduled AI agents with approvals and an audit trail
  • Developers who need tracing, evals and versioned agent configuration in one open-source stack
  • Companies wanting to self-host agents with their own models and credentials

Choose n8n if you need

  • Technical teams that want to self-host automation with Docker, on-prem or air-gapped
  • Builders combining LLM agents, MCP tools and RAG with ordinary app integrations
  • Workflows with many steps, since billing counts executions rather than individual operations

Agenta vs n8n: the questions people ask

Is Agenta cheaper than n8n?

Agenta starts at $29/mo. n8n has a free tier; what its paid plans cost is not confirmed by us yet.

Does Agenta or n8n have a free tier?

Both: Agenta has a free tier, and n8n has a free tier.

Which has a public API, Agenta or n8n?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

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