👾 Make AI Agent vs n8n AI Agent: Key Differences Explained

In this comparison, we examine how Make.com and n8n enable building AI agents that act autonomously and integrate with existing systems.

Both tools are no-code automation builders that allow non-developers connect different apps with each other. We explore their setup, tool integration, workflow design, hosting, pricing, and use cases.

Make offers a polished no‑code visual builder with centralized agent management, while n8n delivers open‑source freedom, LangChain support, and self‑hosting options.

Overview of AI Agents

Make defines agents as entities with a system prompt and connected “tool” scenarios that they can invoke to reach goals. Important to note is that this feature is currently in beta which usually means there could be unexpected bugs - not ideal for a production setup.

In n8n, an AI Agent is represented similarily. You can connect a model, a memory and one or more tools that the agent can access.

Agent Creation & Configuration

On Make, users start by navigating to the AI Agents section, naming the agent, writing its role description, and connecting an LLM provider like OpenAI with an API key.

They then add tool scenarios – self‑contained workflows.

In n8n, users place an AI Agent node in a workflow, attach tool sub‑nodes (one per external service), and configure their model credentials and tool schemas directly in the canvas.

Tool Integration & Ecosystem

Make supports over 2,000 standard apps as tools that agents can call within scenarios. But you can’t connect single apps directly. You can only connect scenarios you built before.

n8n integrates its AI Agent node with 422+ apps and services via LangChain tooling, and offers community‑curated templates for common use cases like WhatsApp chatbots or web scraping. You can connect apps directly or other n8n workflows you built before.

AI Model Support & Flexibility

Make lets users connect to various LLM providers – OpenAI, Azure OpenAI, Claude, etc. – by entering respective API keys, all managed centrally per agent.

It treats every agent uniformly, with no distinct “agent types” to choose.

n8n supports multiple chat models – OpenAI, Anthropic, Groq, Mistral Cloud, and Azure – via its Tools Agent, offering enhanced output parsing and LangChain‑style tool interfaces.

Hosting & Deployment Options

Make AI Agents operate entirely in Make’s cloud environment, with agents and scenarios managed through the Make web app.

In contrast, n8n can run on n8n Cloud under paid plans or self‑host freely using the community edition, giving full control over data and infrastructure.

Pricing & Cost Considerations

Make’s plans are tiered by operation count; AI Agents feature is included on paid plans, and costs scale with usage and scenario runs.

n8n Cloud starts at $20 per month (annually billed) for 2.5k executions, unlimited steps, and five active workflows, with unlimited self‑hosted use at no platform fee.

Both platforms incur separate API usage fees for LLM calls, typically a few cents per query when using OpenAI models.

Conclusion & Recommendations

Choose Make.com if you value a refined no‑code builder, visual agent canvas, and centralized management in a fully managed SaaS.

Opt for n8n when you need open‑source flexibility, self‑hosting, advanced LangChain integrations, and customized workflows with granular control.

Both platforms dramatically reduce time to market for AI‑driven automation and empower technical teams to deliver intelligent solutions.