Kavela vs n8n

1. Building an automation

How n8n does it

The standard way to build in n8n is the canvas: you drag nodes onto it, connect them, and add code where a node does not do what you need ¹. Workflow templates are included on every plan ². n8n aims the product at technical teams ¹, and one independent review says the interface assumes some familiarity with JSON and that debugging means reading execution data in that format ¹⁴.

n8n Assistant shortens this. You describe the workflow, and it plans it, builds it in your project, tests it and helps you fix errors; what it produces is a normal n8n workflow you can open, edit and publish ⁴. It asks for confirmation before high-impact actions such as publishing or deleting ⁶. The Assistant runs on Cloud Starter and Pro and on the self-hosted Community and Business editions, not yet on Enterprise; self-hosting it requires Docker, and it is paid for in Assistant credits ^{3, 4}.

You can also build from outside n8n. Its instance-level MCP server lets Claude, ChatGPT or a coding agent create workflows from a description, then run and test them; an owner or admin turns it on and exposes workflows one at a time ¹⁵. The page does not describe creating credentials or publishing through it ¹⁵. n8n Agents can be used from Slack and Telegram, but they are built in the Agents tab or by the Assistant ⁵.

How Kavela does it

In Kavela you start in a conversation. You tell Kav what you want, in the workspace chat or in Telegram, the way you would brief a colleague: every weekday morning, read the new support emails and draft replies to the billing questions. Kav sets the automation up, connects the apps it needs or asks you to through an Approvals card, sets the trigger and runs it.

Describing a workflow in a chat and getting it built is no longer rare: n8n's Assistant and its MCP server both do a version of it ^{4, 15}. The real difference is how far the agent takes it. n8n's tools hand back a workflow to review, credentials to enter and a publish step to confirm ^{4, 6}. Kav carries the setup through, asking you only through a card when it needs you, runs the work on your own model plan, and when a step needs judgement, an agent does it.

If you can describe the job, that should be enough to get it running.

2. Triggers and schedules

How n8n does it

n8n's Schedule Trigger runs a workflow at intervals of seconds, minutes, hours, days, weeks or months, or on a custom cron expression; the workflow must be saved and published before it runs ⁷. Webhook and queue triggers are on every plan ².

A durable scheduler, generally available since n8n 2.36, stores upcoming runs in the database so a restart does not drop them; self-hosted instances opt in with environment variables ³. One run can last up to 5 minutes on Starter and 40 minutes on Pro ². n8n Agents have their own schedules, hourly to monthly or a custom cron, which you describe in plain language; an agent that watches an event stream continuously is listed as not yet available ^{5, 16}.

How Kavela does it

Kavela automations run on a schedule or on an event, such as a webhook or a merged pull request. You say when, in plain words, and Kav sets the trigger. Any automation can be limited to an active window with a start and an end date, so work tied to a launch or a campaign stops when it ends.

Each run happens in the agent's own cloud computer, which starts when the work starts and sleeps when it stops, so one agent's work never slows another's. The workspace's files persist between runs, so tomorrow's run starts from today's output. There is no cap on how many are switched on at once.

Saying when a job should run is easier than writing a cron expression, and an end date means finished work stops on its own.

3. Your own model plan

How n8n does it

AI steps in n8n run on your own provider credentials or on n8n's Gateway credits ⁸. Gateway credits, added in n8n 2.36, are a prepaid balance for supported models from OpenAI, Anthropic, Gemini and others, billed per request. They are offered on Cloud Starter and Pro only, not on Cloud Enterprise or self-hosted, and when the balance reaches zero the Gateway nodes stop while nodes on your own credentials keep running ^{3, 8}. The pricing page calls this 'AI models without API keys' ².

With your own credentials you can use any provider you have a key for, and n8n's Anthropic credential lists an API key as its only method ^{9, 13}. The docs describe no way to run AI steps on a ChatGPT or Claude consumer subscription ^{8, 9}. One agent turn counts as one execution from your workflow quota ³. If you build through the MCP server from Claude or ChatGPT, that conversation uses your chat app, while the AI steps in the workflow it creates are still billed through a key or Gateway credits ^{8, 15}.

How Kavela does it

Each Kavela agent runs on the plan you choose for it. With your own Claude plan, the unmodified Claude Code runs inside the agent's own cloud computer and you sign in to it yourself, which is the form Anthropic's terms describe for platforms ¹⁷. With a ChatGPT plan, the agent runs Codex instead, and anyone with neither uses Kavela's included Kav AI usage.

Because the choice is per agent, one automation can run on Claude and the next on Codex, and the AI work in your automations draws on the subscriptions you already pay for, with no API key to create.

Most people who automate with AI already pay for Claude or ChatGPT; their automations should be able to use that plan.

4. Work that needs judgement

How n8n does it

n8n has two ways to put a model in charge of a step. The AI Agent node sits inside a workflow. n8n Agents stand on their own, with a model, instructions, tools (n8n nodes, MCP servers, your own workflows and custom tools), skills, sub-agents, knowledge files and memory ^{3, 5}. Agents can search the web, and Gateway tool services include the Browserbase browser service ³. For decisions, a node added on 30 September 2026 returns an answer with a confidence score, so a workflow can branch on fuzzy input or hand off to a person ³.

For email, you give an agent a Gmail or Outlook tool and can make it wait for a person's review before it runs ¹¹. n8n lists what agents cannot do yet: watch an event stream continuously, full multi-agent orchestration, and being called by agents outside n8n; memory across conversations needs a separate OpenAI credential ^{5, 16}. The docs describe no agent that signs in to a web app and tests it by clicking through it, and no lead agent that plans work across a team ⁵.

How Kavela does it

In Kavela, a step that needs judgement is work an agent does, with the tools a person would use. Each agent has its own cloud computer with a shell, files, git and a browser. It can read a customer's email, work out what they are asking and write the reply, or sign in to your app in its browser, go through the sign-up flow and report what broke.

The work belongs to a standing team. Kav, the lead agent, plans the job, hands each part to the right worker agent, follows up and brings back the result, and every task sits on one calendar with its start time, due time and live state. If no worker fits, you describe the job and Kav builds one that follows that process.

The steps that need a decision are often the ones that make an automation fragile, and they are the ones most worth handing to an agent.

5. Connecting your tools

How n8n does it

In n8n you set a credential on each node. On n8n Cloud, listed Google nodes offer a managed 'Sign in with Google'. On a self-hosted instance that option is unavailable: you create a Google Cloud project, enable the APIs, set up a consent screen, create OAuth client credentials and paste in the redirect URL yourself ¹⁰.

The Assistant shows a credential card in the chat for picking or creating a credential, you type the secret on n8n's normal credential screen, and n8n states that credential secrets are never sent to the AI ⁴. n8n supports MCP both ways, with an MCP Client node and an MCP Server Trigger on every plan, and agents can use MCP servers as tools ^{2, 5}. Enterprise adds end-user credentials, in preview, and external secret stores ². The docs describe no flow in which the AI creates an account or obtains a credential itself ⁴.

How Kavela does it

Kavela connections belong to the workspace: connect a service once and every agent can use it. A service can be connected by OAuth sign-in, as an MCP server, with an API key, with custom secrets, or by signing in to it in a live browser you control. Passwords and keys go into the card, never through the model.

You can also leave it to the agent. With Let Kav set it up, the agent reads the service's documentation, works out the right way to connect it and does the setup. If there is no account yet, it creates one, using the workspace's own receive-only inbox to read the verification email.

Connecting a tool is setup work, and the less of it you do by hand, the sooner the automation runs.

6. What it needs from you, and what it delivers

How n8n does it

n8n can make an AI agent's tool wait for a person: the run pauses until a reviewer approves, and the tool runs with the AI's inputs, or denies, and it does not ¹¹. The request goes to the channel you set: n8n chat, Slack, Discord, Telegram, Microsoft Teams, Gmail, WhatsApp Business Cloud, Google Chat or Outlook ¹¹. Send and Wait nodes add approvals at the workflow level; Slack and Telegram approvals take one tap and can be limited to listed approvers, and Slack approvals need the instance reachable over public HTTPS ³. n8n Agents ask for Approve or Reject in their chat on tools you mark sensitive ⁵.

What a workflow produces goes wherever the workflow sends it. n8n keeps execution logs and history, and agent conversations are stored in a Sessions tab ¹⁶. The docs describe no single inbox that gathers approvals from every workflow and agent ¹¹.

How Kavela does it

Kavela collects everything your agents need into one Approvals inbox for the whole workspace. Each request is a typed card you answer where it is: connect an app, sign in to a site in a live browser, approve an action before it goes out, choose between options, or let an agent know the email it was waiting for has arrived. Other work carries on while a card waits.

What agents produce arrives as deliverables attached to the task that made them, from documents and reports to sites and files, listed under Delivered and opened in one click.

When every request lands in one place, checking on ten automations takes as long as checking on one.