Workflow Patterns

Proven architectural patterns for building n8n workflows, based on analysis of real workflow usage.

Pattern Selection Guide

Pattern	Use When	Example
Webhook Processing	Receiving events from external systems	Stripe payment → DB → confirmation email
HTTP API Integration	Fetching data from REST APIs	GitHub issues → Jira tickets
Database Operations	Syncing, querying, ETL workflows	Postgres → transform → MySQL
AI Agent Workflow	Conversational AI, multi-step reasoning	Chat AI with tool access
Scheduled Tasks	Recurring reports, maintenance	Daily analytics → email report

Pattern Statistics

Most common triggers: Webhook (35%), Schedule (28%), Manual (22%), Service triggers (15%) Most common transformations: Set/field mapping (68%), Code/custom logic (42%), IF/conditional (38%), Switch (18%) Most common outputs: HTTP Request (45%), Slack (32%), Database writes (28%), Email (24%)

Pattern 1: Webhook Processing

Most common pattern — 35% of all workflows

Structure

Webhook → Validate → Transform → Respond/Notify

Node List

Webhook — HTTP endpoint (instant trigger)
IF / Switch — Validate incoming data
Set — Map/transform fields
Action node — Slack, Email, HTTP Request, Database
Respond to Webhook — Send HTTP response back to caller

Use Cases

Form submissions (contact forms, sign-ups)
Payment webhooks (Stripe, PayPal)
Git webhooks (GitHub, GitLab push events)
Slack slash commands
Chat integrations

Quick Start Example

Webhook (path: "form-submit", method: POST)
Set (map form fields from $json.body.*)
Slack (post to #notifications)
Respond to Webhook (return 200 OK)

Webhook data is nested under .body.Always access webhook payload fields as {{$json.body.fieldName}}, not {{$json.fieldName}}.

// Webhook receives: {"name": "John", "email": "john@example.com"}

// $json structure from Webhook node:
{
  "headers": {...},
  "params": {},
  "query": {},
  "body": {
    "name": "John",
    "email": "john@example.com"
  }
}

// Correct access:
{{$json.body.name}}    // ✅
{{$json.name}}         // ❌ undefined

Template Reference

The n8n template library has hundreds of webhook processing examples. Search with:

search_templates({searchMode: "by_task", task: "webhook_processing"})

Pattern 2: HTTP API Integration

Structure

Trigger → HTTP Request → Transform → Action → Error Handler

Node List

Trigger — Manual, Schedule, or Webhook
HTTP Request — Fetch from REST API
Split In Batches — Handle large result sets
Set / Code — Transform API response
Action node — Database write, Slack notification, etc.
Error Trigger — Catch and handle failures

Use Cases

Data fetching and synchronization with third-party services
Building data pipelines between systems
Multi-step API orchestration
Converting between service formats (e.g., GitHub → Jira)

Quick Start Example

Manual Trigger (for testing)
HTTP Request (GET /api/users)
Split In Batches (process 100 at a time)
Set (transform user data fields)
Postgres (upsert users)
Loop (back to step 3 until done)

Key Configuration Notes

// HTTP Request with authentication
{
  method: "GET",
  url: "https://api.example.com/users",
  authentication: "predefinedCredentialType",
  nodeCredentialType: "httpHeaderAuth",
  sendQuery: true,
  queryParameters: {
    parameters: [{name: "limit", value: "100"}]
  }
}

// HTTP Request with POST body
{
  method: "POST",
  url: "https://api.example.com/create",
  sendBody: true,          // Required for POST!
  body: {
    contentType: "json",
    content: {
      name: "={{$json.body.name}}",
      email: "={{$json.body.email}}"
    }
  }
}

Template Reference

search_templates({searchMode: "by_nodes", nodeTypes: ["n8n-nodes-base.httpRequest"]})

Pattern 3: Database Operations

Structure

Schedule → Query → Transform → Write → Verify

Node List

Schedule — Trigger on cron schedule
Postgres / MySQL / MongoDB — Read source database
IF — Check if records exist or need updating
Set / Code — Transform and clean data
Postgres / MySQL — Write to target database
Postgres — Update sync timestamp or log result

Use Cases

Database synchronization between systems
ETL (Extract, Transform, Load) workflows
Scheduled reports from database queries
Data backup and archival
Incremental sync (only new/changed records)

Quick Start Example

Schedule (every 15 minutes)
Postgres (query new records since last sync)
IF (check if records exist in target)
MySQL (insert new / update existing)
Postgres (update sync timestamp)

Key Configuration Notes

// Postgres SELECT with parameters
{
  operation: "executeQuery",
  query: "SELECT * FROM users WHERE updated_at > $1",
  additionalFields: {
    queryParams: "={{$json.lastSync}}"
  }
}

// Postgres INSERT / UPSERT
{
  operation: "insert",
  table: "users",
  columns: "id,name,email",
  additionalFields: {
    upsert: true,
    conflictResolution: "id"
  }
}

Pattern 4: AI Agent Workflow

Structure

Trigger → AI Agent (Model + Tools + Memory) → Output

Node List

Webhook / Chat Trigger — Receive user message
AI Agent (nodes-langchain.agent) — Core reasoning node
OpenAI Chat Model — Connected via ai_languageModel
Tool nodes — Connected via ai_tool (HTTP Request, DB Query, etc.)
Window Buffer Memory — Connected via ai_memory
Webhook Response — Send AI reply back to user

Use Cases

Conversational chatbots with tool access
AI assistants that can query databases or call APIs
Content generation with data lookup
Multi-step reasoning and decision-making

Quick Start Example

1. Webhook (receive chat message)
2. AI Agent
   ├─ OpenAI Chat Model    (ai_languageModel)
   ├─ HTTP Request Tool    (ai_tool)
   ├─ Database Tool        (ai_tool)
   └─ Window Buffer Memory (ai_memory)
3. Webhook Response (send AI reply)

AI Connection Types Reference

// Connect language model
{
  type: "addConnection",
  source: "OpenAI Chat Model",
  target: "AI Agent",
  sourceOutput: "ai_languageModel"
}

// Connect a tool
{
  type: "addConnection",
  source: "HTTP Request Tool",
  target: "AI Agent",
  sourceOutput: "ai_tool"
}

// Connect memory
{
  type: "addConnection",
  source: "Window Buffer Memory",
  target: "AI Agent",
  sourceOutput: "ai_memory"
}

Use ai_agents_guide() from the n8n-mcp server for comprehensive AI workflow guidance including connection types, tool configuration, and prompt engineering.

Pattern 5: Scheduled Tasks

Structure

Schedule → Fetch → Process → Deliver → Log

Node List

Schedule Trigger — Cron-based timing
HTTP Request / Database — Fetch fresh data
Code / Set — Aggregate and format data
Email / Slack — Deliver report or notification
Error Trigger → Slack — Notify on failure

Use Cases

Daily/weekly analytics reports emailed to team
Hourly health checks for external services
Nightly database backups
Periodic data synchronization
Maintenance workflows (cleanup, archival)

Quick Start Example

Template #2947 (Weather to Slack):

Schedule (daily at 8 AM)
HTTP Request (fetch weather API)
Set (format weather data)
Slack (post to #weather channel)

// Deploy this template directly:
n8n_deploy_template({
  templateId: 2947,
  name: "Daily Weather to Slack"
})

Schedule Examples

// Every day at 9 AM
{
  rule: {hour: 9}
}

// Every 15 minutes
{
  rule: {minute: {value: 15, mode: "everyX"}}
}

// Every Monday at 8 AM
{
  rule: {dayOfWeek: 1, hour: 8}
}

Data Flow Patterns

Linear
Branching
Parallel
Loop
Error Handler

Trigger → Transform → Action → End

Use when: Simple workflows with a single execution path.

Trigger → IF → [True Path]
              └→ [False Path]

Use when: Different actions based on conditions.

Trigger → [Branch 1] → Merge
       └→ [Branch 2] ↗

Use when: Independent operations that can run simultaneously.

Trigger → Split in Batches → Process → Loop (until done)

Use when: Processing large datasets in chunks.

Main Flow → [Success Path]
         └→ [Error Trigger → Error Handler]

Use when: Need a separate error handling workflow for critical automation.

Common Workflow Components

Triggers

Webhook — HTTP endpoint, instant response to events
Schedule — Cron-based timing for periodic tasks
Manual — Click to execute (testing and admin)
Polling — Check for changes at intervals

Transformation Nodes

Set — Map and transform fields (used in 68% of workflows)
Code — Complex custom logic in JavaScript or Python
IF / Switch — Conditional routing
Merge — Combine multiple data streams

Error Handling

Error Trigger — Catch workflow-level errors
IF — Check for error conditions inline
Stop and Error — Explicit failure node
Continue On Fail — Per-node setting to keep workflow running

Workflow Creation Checklist

Planning Phase

Identify the pattern (webhook, API, database, AI, scheduled)
List required nodes (use search_nodes)
Map data flow: input → transform → output
Plan error handling strategy

Implementation Phase

Create workflow with appropriate trigger
Add data source nodes
Configure authentication/credentials
Add transformation nodes (Set, Code, IF)
Add output/action nodes
Configure error handling

Validation Phase

Validate each node with validate_node
Validate complete workflow with validate_workflow
Test with sample data
Handle edge cases (empty data, API errors)

Deployment Phase

Review workflow settings (execution order, timeout)
Activate using activateWorkflow operation
Monitor first executions
Document workflow purpose and data flow

Common Gotchas

Gotcha	Problem	Solution
Webhook data structure	Can’t access payload fields	Data is under `$json.body.*`
Multiple input items	Node processes all items but you want one	Use “Execute Once” mode or `$json[0].field`
Auth failures	401/403 errors	Configure credentials section, not parameters
Unexpected execution order	Nodes run out of order	Check Settings → Execution Order (use v1)
Expression shows literal	`{{}}` not evaluated	Add `{{}}` around expressions

Best Practices

Do

Start with the simplest pattern that solves your problem
Plan workflow structure before building
Add error handling to every production workflow
Test with sample data before activation
Use descriptive node names
Build iteratively (avg 56s between edits is normal)

Don't

Build complex multi-pattern workflows without clear boundaries
Skip validation before activation
Ignore error scenarios
Hardcode credentials in node parameters
Forget to handle empty data cases
Deploy without testing

​Workflow Patterns

​Pattern Selection Guide

​Pattern Statistics

​Pattern 1: Webhook Processing

​Structure

​Node List

​Use Cases

​Quick Start Example

​Template Reference

​Pattern 2: HTTP API Integration

​Structure

​Node List

​Use Cases

​Quick Start Example

​Key Configuration Notes

​Template Reference

​Pattern 3: Database Operations

​Structure

​Node List

​Use Cases

​Quick Start Example

​Key Configuration Notes

​Pattern 4: AI Agent Workflow

​Structure

​Node List

​Use Cases

​Quick Start Example

​AI Connection Types Reference

​Pattern 5: Scheduled Tasks

​Structure

​Node List

​Use Cases

​Quick Start Example

​Schedule Examples

​Data Flow Patterns

​Common Workflow Components

​Workflow Creation Checklist

​Common Gotchas

​Best Practices

Do

Don't

Workflow Patterns

Pattern Selection Guide

Pattern Statistics

Pattern 1: Webhook Processing

Structure

Node List

Use Cases

Quick Start Example

Template Reference

Pattern 2: HTTP API Integration

Structure

Node List

Use Cases

Quick Start Example

Key Configuration Notes

Template Reference

Pattern 3: Database Operations

Structure

Node List

Use Cases

Quick Start Example

Key Configuration Notes

Pattern 4: AI Agent Workflow

Structure

Node List

Use Cases

Quick Start Example

AI Connection Types Reference

Pattern 5: Scheduled Tasks

Structure

Node List

Use Cases

Quick Start Example

Schedule Examples

Data Flow Patterns

Common Workflow Components

Workflow Creation Checklist

Common Gotchas

Best Practices