n8n-io/n8n

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

181,904 stars TypeScript 10 components

Fair-code workflow automation platform with AI capabilities and visual builder

Workflows are created in the frontend editor, stored as JSON definitions, executed by the core engine, and can trigger external integrations or AI agents

Under the hood, the system uses 3 feedback loops, 4 data pools, 4 control points to manage its runtime behavior.

Structural Verdict

A 10-component fullstack with 0 connections. 11078 files analyzed. Minimal connections — components operate mostly in isolation.

How Data Flows Through the System

Workflows are created in the frontend editor, stored as JSON definitions, executed by the core engine, and can trigger external integrations or AI agents

  1. Workflow Creation — User builds workflow in Vue editor or via API (config: N8N_PERSONALIZATION_ENABLED, N8N_AI_ENABLED)
  2. Workflow Storage — JSON workflow definition stored in database
  3. Execution Trigger — Manual, webhook, or scheduled trigger starts execution (config: EXTERNAL_FRONTEND_HOOKS_URLS)
  4. Node Execution — Core engine executes nodes sequentially based on connections (config: task_timeout, max_concurrency)
  5. AI Processing — AI nodes process using configured models and memory (config: stdlib_allow, external_allow)
  6. Result Output — Execution results stored and returned to client (config: SKIP_STATISTICS_EVENTS)

System Behavior

How the system actually operates at runtime — where data accumulates, what loops, what waits, and what controls what.

Data Pools

Binary Data Store (file-store)
File storage for workflow binary data like images, documents
Workflow Definitions (database)
JSON workflow configurations and metadata
Execution History (database)
Workflow execution results and logs
AI Memory Store (state-store)
Conversational context and agent state

Feedback Loops

Delays & Async Processing

Control Points

Package Structure

This monorepo contains 10 packages:

cli (app)
Main CLI application and backend server for n8n workflow automation platform
editor-ui (app)
Vue-based frontend editor for building workflows visually
nodes-base (library)
Core collection of 400+ integration nodes for various services
core (library)
Core workflow execution engine and runtime services
workflow (library)
Workflow definition, execution logic, and error handling primitives
agents (library)
AI agent framework with LangChain integration for building conversational workflows
ai-node-sdk (library)
SDK for creating AI-powered nodes with chat models and memory capabilities
ai-utilities (library)
Common utilities for AI operations including tokenization, vector stores, and model interfaces
task-runner-python (app)
Python task runner for executing Python code in workflows with security sandboxing
ai-workflow-builder (library)
AI-powered workflow generation and evaluation framework for enterprise features

Technology Stack

Node.js (framework)
Runtime environment for backend services
Vue.js (framework)
Frontend framework for workflow editor
TypeScript (framework)
Primary language for type-safe development
Python (framework)
Task runner for Python code execution
Turbo (build)
Monorepo build system and task runner
pnpm (build)
Package manager with workspace support
LangChain (library)
AI framework for agent and chat implementations
Convict (library)
Configuration schema validation
Jest (testing)
Testing framework for unit and integration tests
ESLint (build)
Code linting with custom rules

Key Components

Configuration

codecov.yml (yaml)

cubic.yaml (yaml)

lefthook.yml (yaml)

pnpm-workspace.yaml (yaml)

Explore the interactive analysis

See the full architecture map, data flow, and code patterns visualization.

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Frequently Asked Questions

What is n8n used for?

Fair-code workflow automation platform with AI capabilities and visual builder n8n-io/n8n is a 10-component fullstack written in TypeScript. Minimal connections — components operate mostly in isolation. The codebase contains 11078 files.

How is n8n architected?

n8n is organized into 5 architecture layers: Frontend Layer, API Layer, Execution Layer, Integration Layer, and 1 more. Minimal connections — components operate mostly in isolation. This layered structure keeps concerns separated and modules independent.

How does data flow through n8n?

Data moves through 6 stages: Workflow Creation → Workflow Storage → Execution Trigger → Node Execution → AI Processing → .... Workflows are created in the frontend editor, stored as JSON definitions, executed by the core engine, and can trigger external integrations or AI agents This pipeline design reflects a complex multi-stage processing system.

What technologies does n8n use?

The core stack includes Node.js (Runtime environment for backend services), Vue.js (Frontend framework for workflow editor), TypeScript (Primary language for type-safe development), Python (Task runner for Python code execution), Turbo (Monorepo build system and task runner), pnpm (Package manager with workspace support), and 4 more. This broad technology surface reflects a mature project with many integration points.

What system dynamics does n8n have?

n8n exhibits 4 data pools (Binary Data Store, Workflow Definitions), 3 feedback loops, 4 control points, 3 delays. The feedback loops handle retry and recursive. These runtime behaviors shape how the system responds to load, failures, and configuration changes.

What design patterns does n8n use?

5 design patterns detected: Dependency Injection, Plugin Architecture, Event-Driven Architecture, Monorepo Structure, Configuration Management.

Analyzed on March 31, 2026 by CodeSea. Written by .