n8n-nodes-ai-workflow-builder

Native-like AI workflow builder for n8n using Claude API. Generate, modify, and refine n8n workflows using natural language - similar experience to n8n's built-in AI Workflow Builder.

Why This Node?

• 🎯 Native-like Experience: Chat refinement, validation, and iterative improvements
• 🧠 Intelligent Context: Uses only relevant n8n nodes (not all 400+)
• 💰 Cost-Effective: Prompt caching reduces costs by ~85%
• 🔧 Auto-fix: Automatically validates and fixes common workflow issues
• 💬 Conversational: Refine workflows through natural conversation
• 📤 Flexible Output: JSON or downloadable file format

Installation

Community Nodes (Recommended)

1. Go to Settings > Community Nodes
2. Select Install
3. Enter n8n-nodes-ai-workflow-builder
4. Agree to risks and install

Manual Installation

npm install n8n-nodes-ai-workflow-builder

Prerequisites

• n8n version 0.187.0 or higher
• Claude API key from Anthropic

Quick Start

1. Setup Credentials

1. Get your API key from Anthropic Console
2. In n8n: Credentials > New > Claude API
3. Enter your API key
4. Choose model: Claude Sonnet 4.5 (recommended)

2. Add the Node

1. Create a new workflow
2. Add Manual Trigger node
3. Add AI Workflow Builder node
4. Configure and execute!

Operations

🆕 Generate Workflow

Create a brand new workflow from a natural language description.

Example:

Create a workflow that sends me a Slack message every morning at 9 AM
with the weather forecast for London

Output:

• Complete n8n workflow JSON
• Step-by-step import instructions
• Validation results (auto-fixed if needed)
• Token usage and cost breakdown

💬 Chat Refinement (NEW!)

Native-like iterative refinement - The closest experience to n8n's built-in AI builder!

How it works:

1. Generate initial workflow (or start with existing one)
2. Switch to "Chat Refinement" mode
3. Paste previous workflow JSON
4. Send refinement message: "Add error handling"
5. Get updated workflow
6. Continue refining iteratively!

Example flow:

1st message: "Create a Slack notification workflow"
2nd message: "Add error retry logic"
3rd message: "Make it run every hour"
4th message: "Add logging to a database"

Each iteration remembers context and builds on previous changes!

✏️ Modify Workflow

One-time modification of an existing workflow.

Example:

Add error handling to all HTTP Request nodes and send
notifications to Slack on failure

📖 Explain Workflow

Get a detailed explanation of what a workflow does.

Great for:

• Understanding complex workflows
• Documentation
• Onboarding team members
• Identifying issues or improvements

Comparison to Native n8n AI Builder

Feature	Native Builder	This Community Node
Chat Interface	Built-in modal	✅ Chat Refinement mode
Iterative Refinement	Real-time canvas	✅ Via conversation history
Workflow Validation	Automatic	✅ With auto-fix
Context Awareness	Full n8n knowledge	✅ Intelligent context (relevant nodes only)
Direct Canvas Creation	Yes	❌ Manual import (community node limitation)
Cost Optimization	N/A	✅ 85% savings with prompt caching
Export Options	Automatic	✅ JSON + downloadable file
Conversation History	Built-in	✅ Manual copy/paste

Advanced Features

Workflow Validation ✅

Automatically checks for:

• Missing trigger nodes
• Invalid node positions
• Missing connections
• Required workflow fields
• Proper node structure

Auto-fix mode (enabled by default):

• Adds missing workflow name
• Fixes invalid positions
• Creates connections object
• Ensures all required fields

Multiple Output Formats 📤

Choose how to receive your workflow:

1. Workflow JSON: Copy and import manually
2. Export File: Base64 downloadable file
3. Both: Get both formats

Intelligent Context System 🧠

Instead of sending all 400+ n8n nodes to Claude:

1. Extracts keywords from your description
2. Finds 3-10 most relevant keywords
3. Retrieves only relevant nodes (10-15 max)
4. Includes similar workflow examples
5. Result: Better quality, lower cost!

Example:

• Your request: "Create a Slack notification workflow"
• Keywords extracted: ["slack", "notification", "trigger", "message"]
• Nodes included: Slack, Webhook, Schedule Trigger, Manual Trigger, Code
• Example shown: "Webhook to Slack" pattern

Prompt Caching 💰

Massive cost savings through Anthropic's prompt caching:

Request	Input Tokens	Cached	Cost
First	~3,300	0	$0.012-$0.015
Second	~100-200	~3,200	$0.002-$0.003
Third+	~100-200	~3,200	$0.002-$0.003
Savings			~85%

Cache duration: 5 minutes

Usage Examples

Example 1: Iterative Chat Refinement

Step 1 - Generate:
  "Create a workflow that sends Slack notifications"

Step 2 - Refine (Chat mode):
  Previous Workflow: [paste from step 1]
  Message: "Add error handling with retries"

Step 3 - Refine again:
  Previous Workflow: [paste from step 2]
  Conversation History: [paste from step 2]
  Message: "Make it run every hour"

Step 4 - Final refinement:
  Previous Workflow: [paste from step 3]
  Conversation History: [paste from step 3]
  Message: "Add logging to PostgreSQL"

Result: Fully refined workflow with all features!

Example 2: Daily Report Workflow

Description:

Create a workflow that runs daily at 8 AM, fetches data from
our PostgreSQL database, generates a summary report, and emails
it to the team at team@company.com

Generated:

• Schedule Trigger (8 AM daily)
• PostgreSQL query node
• Code node (data formatting)
• Gmail send node

Validation: ✅ All checks passed
Cost: $0.0128 (first request)
Time: ~5 seconds

Example 3: Customer Support Automation

Description:

Build a workflow that listens for new Intercom messages,
uses AI to categorize them, and routes urgent issues to
PagerDuty while others go to a Slack channel

Generated:

• Webhook trigger
• AI Agent (LangChain) for classification
• IF node for routing
• PagerDuty + Slack nodes

Refinement via Chat:

"Add a cooldown to prevent spam triggering PagerDuty"

Cost: $0.0024 (cached)

Example 4: Social Media Monitoring

Description:

Monitor Twitter for mentions of @ourcompany, analyze sentiment
with AI, and post positive ones to our #social-media Slack channel

Generated:

• Twitter Trigger (@ourcompany mentions)
• AI sentiment analysis (LangChain)
• IF node (positive sentiment filter)
• Slack post node

Advanced Options

Include Examples (default: on)

• Includes similar workflow patterns
• Helps Claude learn from real examples
• ~500 additional tokens

Include Node Details (default: on)

• Adds detailed node documentation
• Relevant nodes only (not all 400+)
• ~2,000 additional tokens

Temperature (default: 0.7)

• 0.0 = Deterministic (same input → same output)
• 0.7 = Balanced (recommended)
• 1.0 = Creative (more variation)

Validate Workflow (default: on)

• Checks workflow structure
• Identifies issues
• Shows validation results

Auto-fix Issues (default: on)

• Automatically fixes common problems
• Adds missing fields
• Corrects positions and connections

Tips for Best Results

✅ DO:

• Be specific: Include timing, tools, conditions
• Name services: "Slack", "PostgreSQL", not just "database"
• Describe logic: "If urgent then X, otherwise Y"
• Use Chat mode: For complex workflows, iterate!
• Check validation: Review auto-fix suggestions

❌ DON'T:

• Be vague: "Make a workflow"
• Skip details: "Send a notification" (to where?)
• Ignore errors: Always review validation results
• Forget credentials: Remember to configure after import

Pricing

Uses your own Claude API key. See Anthropic Pricing.

Typical costs:

• Simple workflow: $0.01 - $0.05 (first request)
• Simple workflow: $0.002 - $0.003 (cached)
• Complex workflow: $0.05 - $0.20 (first request)
• Modifications: $0.01 - $0.10
• Chat refinement: $0.002 - $0.005 per message (cached)

Monthly estimates (based on usage):

• 10 workflows/month: ~$0.20 - $1.00
• 50 workflows/month: ~$1.00 - $5.00
• 200 workflows/month: ~$5.00 - $20.00

With caching, costs drop by ~85% after first request!

Troubleshooting

"No trigger node found"

The workflow needs a trigger to start execution. Add "trigger" to your description.

"Invalid workflow JSON"

The AI response couldn't be parsed. Try:

1. Enable "Auto-fix Issues"
2. Regenerate with more specific description
3. Use Chat mode to refine

"High token usage"

• Disable "Include Node Details" for simpler workflows
• Use shorter descriptions
• Prompt caching helps after first request

Import errors in n8n

• Check validation results
• Enable "Auto-fix Issues"
• Manually verify node connections
• Configure credentials for nodes that need them

Architecture

This node uses a sophisticated multi-layer context system:

1. Core System Prompt (~800 tokens) - n8n structure basics
2. Node Database (variable) - Only relevant nodes
3. Workflow Examples (~500 tokens) - Similar patterns
4. Context Builder - Intelligent keyword extraction
5. Prompt Caching - 85% cost savings

Total context: ~3,300 tokens (first request), ~100-200 tokens (cached)

Support

• 🐛 Report Issues
• 💬 n8n Community
• 📖 Anthropic Docs
• 📘 n8n Docs

Contributing

Contributions welcome! Areas to improve:

• Add more nodes to the database
• Add more workflow examples
• Improve validation logic
• Add more output formats
• Better error handling

License

MIT

Author

Hicham Char - GitHub

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Built with ❤️ using Claude Code