Repository: Zie619/n8n-workflows
Stars: 53806
CLAUDE.md
n8n-workflows Repository
#
Overview
This repository contains a collection of n8n workflow automation files. n8n is a workflow automation tool that allows creating complex automations through a visual node-based interface. Each workflow is stored as a JSON file containing node definitions, connections, and configurations.
#
Repository Structure
``
text
text
text
n8n-workflows/
βββ workflows/
Main directory containing all n8n workflow JSON files
β βββ *.json
Individual workflow files
βββ README.md
Repository documentation
βββ claude.md
This file
- AI assistant context
βββ [other files]
Additional configuration or documentation files
`text
text
text
#
Workflow File Format
Each workflow JSON file contains:
- name: Workflow identifier
- nodes: Array of node objects defining operations
- connections: Object defining how nodes are connected
- settings: Workflow-level configuration
- staticData: Persistent data across executions
- tags: Categorization tags
- createdAt/updatedAt: Timestamps
#
Common Node Types
- Trigger Nodes: webhook, cron, manual
- Integration Nodes: HTTP Request, database connectors, API integrations
- Logic Nodes: IF, Switch, Merge, Loop
- Data Nodes: Function, Set, Transform Data
- Communication: Email, Slack, Discord, etc.
#
Working with This Repository
#
#
For Analysis Tasks
When analyzing workflows in this repository:
1. Parse JSON files to understand workflow structure
2. Examine node chains to determine functionality
3. Identify external integrations and dependencies
4. Consider the business logic implemented by node connections
#
#
For Documentation Tasks
When documenting workflows:
1. Verify existing descriptions against actual implementation
2. Identify trigger mechanisms and schedules
3. List all external services and APIs used
4. Note data transformations and business logic
5. Highlight any error handling or retry mechanisms
#
#
For Modification Tasks
When modifying workflows:
1. Preserve the JSON structure and required fields
2. Maintain node ID uniqueness
3. Update connections when adding/removing nodes
4. Test compatibility with n8n version requirements
#
Key Considerations
#
#
Security
- Workflow files may contain sensitive information in webhook URLs or API configurations
- Credentials are typically stored separately in n8n, not in the workflow files
- Be cautious with any hardcoded values or endpoints
#
#
Best Practices
- Workflows should have clear, descriptive names
- Complex workflows benefit from documentation nodes or comments
- Error handling nodes improve reliability
- Modular workflows (calling sub-workflows) improve maintainability
#
#
Common Patterns
- Data Pipeline: Trigger β Fetch Data β Transform β Store/Send
- Integration Sync: Cron β API Call β Compare β Update Systems
- Automation: Webhook β Process β Conditional Logic β Actions
- Monitoring: Schedule β Check Status β Alert if Issues
#
Helpful Context for AI Assistants
When assisting with this repository:
1. Workflow Analysis: Focus on understanding the business purpose by examining the node flow, not just individual nodes.
2. Documentation Generation: Create descriptions that explain what the workflow accomplishes, not just what nodes it contains.
3. Troubleshooting: Common issues include:
- Incorrect node connections
- Missing error handling
- Inefficient data processing in loops
- Hardcoded values that should be parameters
4. Optimization Suggestions:
- Identify redundant operations
- Suggest batch processing where applicable
- Recommend error handling additions
- Propose splitting complex workflows
5. Code Generation: When creating tools to analyze these workflows:
- Handle various n8n format versions
- Account for custom nodes
- Parse expressions in node parameters
- Consider node execution order
#
Repository-Specific Information
[Add any specific information about your workflows, naming conventions, or special considerations here]
#
Version Compatibility
- n8n version: [Specify the n8n version these workflows are compatible with]
- Last updated: [Date of last major update]
- Migration notes: [Any version-specific considerations]
-
-
-
δΈζREADME.md
n8n Workflow Collection
<div align="center">
!n8n Workflows
!Workflows
!Integrations
!License

The Ultimate Collection of n8n Automation Workflows
Browse Online Β· Documentation Β· Contributing Β· License
</div>
---
<div align="center">
<a href="https://github.com/Trusera/ai-bom">
<img src="https://raw.githubusercontent.com/Trusera/ai-bom/main/assets/logo.png" alt="AI-BOM Logo" width="100" />
</a>
<h2>NEW: Scan Your n8n Workflows for AI Security Risks</h2>
<a href="https://github.com/Trusera/ai-bom">
<img src="https://img.shields.io/badge/AI--BOM-Scan%20Now-ff4444?style=for-the-badge&logoColor=white" alt="AI-BOM" />
</a>
<a href="https://github.com/Trusera/ai-bom">
<img src="https://img.shields.io/badge/Open%20Source-Apache%202.0-blue?style=for-the-badge" alt="Open Source" />
</a>
<a href="https://github.com/Trusera/ai-bom">
<img src="https://img.shields.io/badge/First%20n8n%20AI%20Scanner-Ever-brightgreen?style=for-the-badge" alt="First Ever" />
</a>
</div>
<table>
<tr>
<td width="65%">
Your workflows contain AI β do you know what's hiding in them?
We built AI-BOM because we scanned our own 4,343 workflows and found hardcoded API keys, unauthenticated AI agents, and MCP clients connecting to unknown servers β all invisible to existing security tools.
AI-BOM is the first and only tool that scans n8n workflows for AI security risks.
`bash
pip install ai-bom
ai-bom scan ./workflows/
`
One command finds every AI Agent node, LLM integration, MCP client, hardcoded credential, and dangerous tool combination β then gives you a risk score and a compliance-ready report.
EU AI Act deadline: August 2025. You need an AI inventory.
<a href="https://github.com/Trusera/ai-bom"><strong>Get AI-BOM (free & open source) →</strong></a>
</td>
<td width="35%" align="center">
<a href="https://github.com/Trusera/ai-bom">
<img src="https://raw.githubusercontent.com/Trusera/ai-bom/main/assets/maskot.png" alt="AI-BOM Mascot" width="220" />
</a>
<br />
<sub><strong>AI-BOM</strong> by <a href="https://trusera.dev">Trusera</a></sub>
<br />
<sub>Securing the Agentic Service Mesh</sub>
</td>
</tr>
</table>
<details>
<summary><strong>What does AI-BOM detect in n8n workflows? (click to expand)</strong></summary>
<br />
| Risk | Severity | What it finds |
|------|----------|---------------|
| AI Agent nodes | CRITICAL | Agents connected to LLMs with tool access β can execute code |
| Hardcoded credentials | CRITICAL | API keys in workflow JSON instead of credential store |
| Dangerous tool combos | CRITICAL | Agents with Code Execution + HTTP Request = RCE risk |
| MCP clients | HIGH | Model Context Protocol connections to external servers |
| Unauthenticated webhooks | HIGH | Webhook triggers exposed to the internet without auth |
| Agent chains | HIGH | Execute Workflow linking agents without input validation |
Beyond n8n, AI-BOM also scans source code (Python, JS, TS, Java, Go, Rust, Ruby), Docker configs, cloud infrastructure (Terraform, CloudFormation), and network endpoints β 21+ AI SDKs detected across 7 languages.
Output formats: CycloneDX SBOM | SARIF (GitHub Code Scanning) | HTML Dashboard | Markdown | JSON
</details>
---
What's New
Latest Updates (November 2025)
- Enhanced Security: Full security audit completed, all CVEs resolved
- Docker Support: Multi-platform builds for linux/amd64 and linux/arm64
- GitHub Pages: Live searchable interface at zie619.github.io/n8n-workflows
- Performance: 100x faster search with SQLite FTS5 integration
- Modern UI: Completely redesigned interface with dark/light mode
---
Quick Access
Use Online (No Installation)
Visit zie619.github.io/n8n-workflows for instant access to:
- Smart Search β Find workflows instantly
- 15+ Categories β Browse by use case
- Mobile Ready β Works on any device
- Direct Downloads β Get workflow JSONs instantly
---
Features
<table>
<tr>
<td width="50%">
By The Numbers
- 4,343 Production-Ready Workflows
- 365 Unique Integrations
- 29,445 Total Nodes
- 15 Organized Categories
- 100% Import Success Rate
</td>
<td width="50%">
Performance
- < 100ms Search Response
- < 50MB Memory Usage
- 700x Smaller Than v1
- 10x Faster Load Times
- 40x Less RAM Usage
</td>
</tr>
</table>
---
Local Installation
Prerequisites
- Python 3.9+
- pip (Python package manager)
- 100MB free disk space
Quick Start
`bash
Clone the repository
git clone https://github.com/Zie619/n8n-workflows.git
cd n8n-workflows
Install dependencies
pip install -r requirements.txt
Start the server
python run.py
Open in browser
http://localhost:8000
`
Docker Installation
`bash
Using Docker Hub
docker run -p 8000:8000 zie619/n8n-workflows:latest
Or build locally
docker build -t n8n-workflows .
docker run -p 8000:8000 n8n-workflows
`
---
Documentation
API Endpoints
| Endpoint | Method | Description |
|----------|--------|-------------|
| / | GET | Web interface |
| /api/search | GET | Search workflows |
| /api/stats | GET | Repository statistics |
| /api/workflow/{id} | GET | Get workflow JSON |
| /api/categories | GET | List all categories |
| /api/export | GET | Export workflows |
Search Features
- Full-text search across names, descriptions, and nodes
- Category filtering (Marketing, Sales, DevOps, etc.)
- Complexity filtering (Low, Medium, High)
- Trigger type filtering (Webhook, Schedule, Manual, etc.)
- Service filtering (365+ integrations)
---
Architecture
`mermaid
graph LR
A[User] --> B[Web Interface]
B --> C[FastAPI Server]
C --> D[SQLite FTS5]
D --> E[Workflow Database]
C --> F[Static Files]
F --> G[Workflow JSONs]
`
Tech Stack
- Backend: Python, FastAPI, SQLite with FTS5
- Frontend: Vanilla JS, Tailwind CSS
- Database: SQLite with Full-Text Search
- Deployment: Docker, GitHub Actions, GitHub Pages
- Security: Trivy scanning, CORS protection, Input validation
---
Repository Structure
`
n8n-workflows/
βββ workflows/ # 4,343 workflow JSON files
β βββ [category]/ # Organized by integration
βββ docs/ # GitHub Pages site
βββ src/ # Python source code
βββ scripts/ # Utility scripts
βββ api_server.py # FastAPI application
βββ run.py # Server launcher
βββ workflow_db.py # Database manager
βββ requirements.txt # Python dependencies
`
---
Contributing
We love contributions! Here's how you can help:
Ways to Contribute
- Report bugs via Issues
- Suggest features in Discussions
- Improve documentation
- Submit workflow fixes
- Star the repository
Development Setup
`bash
Fork and clone
git clone https://github.com/YOUR_USERNAME/n8n-workflows.git
Create branch
git checkout -b feature/amazing-feature
Make changes and test
python run.py --debug
Commit and push
git add .
git commit -m "feat: add amazing feature"
git push origin feature/amazing-feature
Open PR
``
---
Security
Security Features
- Path traversal protection
- Input validation & sanitization
- CORS protection
- Rate limiting
- Docker security hardening
- Non-root container user
- Regular security scanning
Reporting Security Issues
Please report security vulnerabilities to the maintainers via Security Advisory.
---
License
This project is licensed under the MIT License - see the LICENSE file for details.
---
Support
If you find this project helpful, please consider:
<div align="center">


</div>
---
<div align="center">
!GitHub stars
!GitHub forks
!GitHub watchers
!GitHub issues
!GitHub last commit
</div>
---
<div align="center">
Star us on GitHub β it motivates us a lot!
Made with care by Zie619 and contributors
<br />
<a href="https://github.com/Trusera/ai-bom">
<img src="https://raw.githubusercontent.com/Trusera/ai-bom/main/assets/logo.png" alt="AI-BOM" width="50" />
</a>
AI-BOM β Discover every AI agent, model, and API hiding in your infrastructure.
<br />
Open source by Trusera β Securing the Agentic Service Mesh.
</div>