n8n-workflow-patterns

# n8n Workflow Patterns

Proven architectural patterns for building n8n workflows.

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## The 5 Core Patterns

Based on analysis of real workflow usage:

1. **[Webhook Processing](webhook_processing.md)** (Most Common)
   - Receive HTTP requests → Process → Output
   - Pattern: Webhook → Validate → Transform → Respond/Notify

2. **[HTTP API Integration](http_api_integration.md)**
   - Fetch from REST APIs → Transform → Store/Use
   - Pattern: Trigger → HTTP Request → Transform → Action → Error Handler

3. **[Database Operations](database_operations.md)**
   - Read/Write/Sync database data
   - Pattern: Schedule → Query → Transform → Write → Verify

4. **[AI Agent Workflow](ai_agent_workflow.md)**
   - AI agents with tools and memory
   - Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output

5. **[Scheduled Tasks](scheduled_tasks.md)**
   - Recurring automation workflows
   - Pattern: Schedule → Fetch → Process → Deliver → Log

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## Pattern Selection Guide

### When to use each pattern:

**Webhook Processing** - Use when:
- Receiving data from external systems
- Building integrations (Slack commands, form submissions, GitHub webhooks)
- Need instant response to events
- Example: "Receive Stripe payment webhook → Update database → Send confirmation"

**HTTP API Integration** - Use when:
- Fetching data from external APIs
- Synchronizing with third-party services
- Building data pipelines
- Example: "Fetch GitHub issues → Transform → Create Jira tickets"

**Database Operations** - Use when:
- Syncing between databases
- Running database queries on schedule
- ETL workflows
- Example: "Read Postgres records → Transform → Write to MySQL"

**AI Agent Workflow** - Use when:
- Building conversational AI
- Need AI with tool access
- Multi-step reasoning tasks
- Example: "Chat with AI that can search docs, query database, send emails"

**Scheduled Tasks** - Use when:
- Recurring reports or summaries
- Periodic data fetching
- Maintenance tasks
- Example: "Daily: