n8n is a workflow automation and AI agent builder for technical teams, run in n8n's cloud or self-hosted, and priced by workflow executions rather than seats.
n8n connects a company's apps, APIs and AI models in workflows, so AI agents run inside the processes that already move its data. n8n GmbH, founded by Jan Oberhauser in 2019, develops it from its Berlin headquarters. Each workflow is a chain of nodes on one canvas, and an agent is one node in that chain. The same software runs in n8n's cloud or on a company's own servers through the self-hosted Community edition. The AI Agent node takes a chat model from the provider the team chooses, a memory for the conversation and a set of tools. Tools can be another workflow through the Call n8n Workflow Tool, an HTTP request, or a function written in the Custom Code Tool. The AI Agent Tool lets a root agent hand work to other agents, and vector store nodes give each agent documents to retrieve from. The Structured Output Parser holds replies to a JSON Schema, while the Guardrails node checks text going into and out of a model. The MCP Client node uses tools over the Model Context Protocol, and the MCP Server Trigger offers a workflow to other AI clients. n8n suits technical teams that build their own automations, from solo builders with workflows in production to organisations with strict compliance and governance needs. Companies that must keep data on their own infrastructure can self-host it, and the Community edition runs without a subscription. Every plan includes unlimited users and workflows, and the bill follows the number of workflow executions, however many steps each one has. n8n hosts the Starter and Pro plans, the Business plan is for self-hosted companies, and Enterprise is arranged with sales in either form. A support team can put the Chat Trigger's embedded chat on its website and ground the agent in documents held in Qdrant. An operations team can start a workflow from a Webhook node, have an agent draft a reply and wait for a Slack approval. Developers return an agent's answer through the Respond to Webhook node, which turns a workflow into an endpoint other software calls. Metric-based evaluations score the workflow's output over time, and workflow history restores an earlier version when an edit falls short. n8n gives a team one canvas where its automations and its AI agents run as parts of the same workflow.
Pricing
View plans-
Community edition
Free
- Free, self-hosted on your own infrastructure
- Almost the complete feature set of n8n
- LangSmith tracing available on self-hosted instances
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Starter
$24 per month
$20 a month billed annually; $24 billed monthly
- Hosted by n8n
- 2,500 workflow executions a month with unlimited steps
- Unlimited users, workflows and integrations
- 5 concurrent executions; executions run for up to 5 minutes
- Agents, MCP and AI nodes; AI models without your own API keys
- 1,600 Assistant credits a month
- 1 shared project; forum support
- Light evaluations on 1 workflow
- 2,500 saved executions with 2.5 GB of storage
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Pro
$60 per month
$50 a month billed annually; $60 billed monthly
- Hosted by n8n
- 10,000 workflow executions a month with unlimited steps
- Everything in Starter, plus 3 shared projects and admin roles
- Up to 50 concurrent executions; executions run for up to 40 minutes
- Metric-based evaluations
- Workflow history, kept five days on Cloud Pro
- Up to 9,600 Assistant credits a month; 7 days of insights
- 25,000 saved executions with 25 GB of storage
- 14-day Cloud trial with Pro features, no credit card required
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Business
$960 per month
$800 a month billed annually; $960 billed monthly
- Self-hosted only
- 40,000 workflow executions a month with unlimited steps
- For companies with fewer than 100 employees
- Everything in Pro, plus version control using Git and 30 days of insights
- Start-up Plan: 50% off Business for companies under 20 employees
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Enterprise
Custom pricing
- Contact sales; no public price
- Hosted by n8n or self-hosted; custom number of workflow executions
- Everything in Business, plus unlimited shared projects
- 200+ concurrent executions; executions run for up to 40 minutes
- 365 days of insights; external secret store integration
- 50,000 saved executions with 50 GB of storage
- Pay by invoice; sales-assisted procurement
Features
- Included: Visual agent workflow canvas
- Included: Custom tool and function definitions
- Included: Model provider choice per agent
- Included: Retrieval-augmented knowledge bases
- Included: Multi-agent handoff and delegation
- Included: Conversation state and checkpointing
- Included: Structured output schema validation
- Included: Input and output guardrails
- Included: Human-in-the-loop approval steps
- Not included: Built-in execution tracing
- Included: Prompt versioning in the builder
- Included: Agent evaluation and test suites
- Included: MCP server support
- Included: Webhook and event triggers
- Not included: Code-first SDK
- Included: Deploy an agent as an API endpoint
- Included: Embeddable agent chat widget
- Included: Self-hosted agent runtime
Additional Features
- Visual workflow editor with an AI Agent node
- Chat model choice per agent, including OpenAI, Anthropic, Gemini and Ollama
- Conversation memory for agents
- Call n8n Workflow Tool
- Custom Code Tool for agent functions
- HTTP Request tool
- AI Agent Tool for multi-agent orchestration
- Vector store nodes for retrieval-augmented generation
Best for
- technical teams that build and maintain their own automations
- companies that must run agents on their own infrastructure
- teams adding AI agents to existing business process automations
- teams that want unlimited users with billing by workflow executions
- solo builders and small teams running automations in production
- self-hosting companies with fewer than 100 employees on the Business plan
- organisations with strict compliance and governance needs
Use cases
- building an AI agent that calls internal tools and APIs
- answering customer questions from company documents in a vector store
- routing an agent's tool calls to a person for approval in Slack
- exposing a workflow to AI assistants as an MCP server
- starting an agent from a webhook or an app event
- returning an agent's answer to an HTTP caller
- embedding a support chat on a website
- coordinating specialist agents under one root agent
- holding model replies to a JSON Schema
- scoring an AI workflow's output with metrics before and after a change
- pausing a long workflow until an outside event resumes it
- syncing data between business apps and databases
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