Understanding Nodes

What is a node?

A node is a single step in your workflow that performs a specific action. Think of nodes as individual LEGO pieces that you connect together to build something powerful. Each node:

Takes inputs (data to process)
Performs an action (scrape, transform, analyze, etc.)
Produces outputs (results to pass to the next node)

Anatomy of a node

Connection points

Every node has connection points:

Input points (left side): Where data enters the node

Node types by function

Type	What it does	Examples
Input	Accepts user input	Text Input
AI	Uses AI models	LLM, AI Agent
Integrations	Fetches data	Web Scraper, Google Sheets
Tools	Modifies data	Find & Replace, Merge, Controls flow

Configuring nodes

Click on any node to open its configuration panel on the node.

Required fields

Fields marked with a red asterisk (*) are required. The node won’t run without them.

URL *: https://example.com

Using variables

Instead of hardcoding values, use variables to pass data from other nodes:

URL: {{url}}

The {{text}} syntax means “use the output value from the node named text”.

Learn more about variables in the Variables guide.

Working with inputs

Static values

Enter values directly in the configuration:

Temperature: 0.7
Max Tokens: 1000

Dynamic values from other nodes

Reference outputs from previous nodes:

Content: {{WebScraper}}

Combining static and dynamic

You can mix both in text fields:

Summarize this article about {{topic}}:

Understanding outputs

Every node produces an output that can be used by subsequent nodes.

Output structure

Most nodes output a JSON object with specific fields:

{
  "status": "success",
  "data": "The scraped content...",
  "metadata": {
    "url": "https://example.com",
    "timestamp": "2024-01-15T10:30:00Z"
  }
}

Node categories

AI Nodes

Leverage powerful AI models for text generation, analysis, and more.

LLM

Generate text with GPT, Claude, or Gemini

AI Agent

Autonomous AI that uses tools

Data Source Nodes

Connect to external data sources.

Google Sheets

Read and write spreadsheet data

Web Scraper

Extract content from websites

Tools Nodes

Transform and manipulate data.

Find & Replace

Search and replace text patterns

JSON Path Extractor

Extract data from JSON

Control Flow Nodes

Control how your workflow executes.

Loop

Repeat actions for each item

Conditional

Branch based on conditions

Best practices

Keep nodes focused

Each node should do one thing well. If a node is doing too much, split it into multiple nodes.

Good
Avoid

Web Scraper → Extract text
LLM → Summarize
Google Sheets → Save results

One mega-node that scrapes, 
summarizes, AND saves

Name your nodes

Give nodes descriptive names by clicking on their title:

❌ LLM_0
✅ Summarize Article

Test incrementally

After adding each node, run your workflow to verify it works before adding more.

Start Here

Fundamentals

Use Cases

What is a node?

Anatomy of a node

Connection points

Node types by function

Configuring nodes

Required fields

Using variables

Working with inputs

Static values

Dynamic values from other nodes

Combining static and dynamic

Understanding outputs

Output structure

Node categories

AI Nodes

LLM

AI Agent

Data Source Nodes

Google Sheets

Web Scraper

Tools Nodes

Find & Replace

JSON Path Extractor

Control Flow Nodes

Loop

Conditional

Best practices

Keep nodes focused

Name your nodes

Test incrementally

Troubleshooting

Node shows an error

Output is unexpected

Next steps

Variables

Workflows

Start Here

Fundamentals

Use Cases

​What is a node?

​Anatomy of a node

​Connection points

​Node types by function

​Configuring nodes

​Required fields

​Using variables

​Working with inputs

​Static values

​Dynamic values from other nodes

​Combining static and dynamic

​Understanding outputs

​Output structure

​Node categories

​AI Nodes

LLM

AI Agent

​Data Source Nodes

Google Sheets

Web Scraper

​Tools Nodes

Find & Replace

JSON Path Extractor

​Control Flow Nodes

Loop

Conditional

​Best practices

​Keep nodes focused

​Name your nodes

​Test incrementally

​Troubleshooting

​Node shows an error

​Output is unexpected

​Next steps

Variables

Workflows

What is a node?

Anatomy of a node

Connection points

Node types by function

Configuring nodes

Required fields

Using variables

Working with inputs

Static values

Dynamic values from other nodes

Combining static and dynamic

Understanding outputs

Output structure

Node categories

AI Nodes

Data Source Nodes

Tools Nodes

Control Flow Nodes

Best practices

Keep nodes focused

Name your nodes

Test incrementally

Troubleshooting

Node shows an error

Output is unexpected

Next steps