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hew

n8n Video Compilation MCP Server

by hew
README.md
# ๐Ÿฅ Insurance Claims Processing Automation Demo

> **Transform manual claims processing from 3 hours to 3 minutes with AI-powered automation**

This n8n workflow demonstrates how insurance companies can automate their claims processing with AI, reducing processing time by 90% while improving fraud detection and customer communication.

## ๐ŸŽฏ Demo Impact

**For a company processing 500 claims/month:**
- **Time savings**: 1,500 hours/month โ†’ 125 hours/month  
- **Cost savings**: $75,000/month โ†’ $6,750/month
- **Annual savings**: ~$819,000
- **ROI**: 13,600% (after automation costs)

## ๐Ÿš€ Quick Start (5 Minutes)

### Prerequisites
- Docker installed on your machine
- OpenAI API key (get from [platform.openai.com](https://platform.openai.com/api-keys))
- Email account for notifications

### 1. Start the Demo
```bash
# Clone or download this repository
# Navigate to the project directory
./start-demo.sh
```

### 2. Access n8n
- Open: http://localhost:5678
- Username: `admin`
- Password: `insurance_demo_2024`

### 3. Import the Workflow
1. Click "Add Workflow" 
2. Menu (โ‹ฏ) โ†’ "Import from File"
3. Upload `insurance-claims-workflow.json`

### 4. Configure Credentials
1. **OpenAI**: Settings โ†’ Credentials โ†’ Add โ†’ OpenAI API
2. **Email**: Settings โ†’ Credentials โ†’ Add โ†’ Email (SMTP)

### 5. Activate & Test
1. Click "Active" toggle
2. Run: `./test-claims.sh`
3. Watch the magic happen! โœจ

## ๐Ÿ“ Project Files

```
n8n-money/
โ”œโ”€โ”€ ๐Ÿ“Š insurance-claims-workflow.json    # Main n8n workflow
โ”œโ”€โ”€ ๐Ÿ“‹ demo-presentation.md             # Sales presentation slides  
โ”œโ”€โ”€ ๐Ÿงช sample-claim-data.json           # Test scenarios
โ”œโ”€โ”€ โš™๏ธ docker-compose.yml               # Easy Docker setup
โ”œโ”€โ”€ ๐Ÿš€ start-demo.sh                    # One-click startup
โ”œโ”€โ”€ ๐Ÿงช test-claims.sh                   # Automated testing
โ”œโ”€โ”€ ๐Ÿ“– setup-guide.md                   # Detailed setup guide
โ”œโ”€โ”€ ๐Ÿ“– local-setup-guide.md             # Local installation guide
โ””โ”€โ”€ ๐Ÿ“– README.md                        # This file
```

## ๐Ÿ”„ Workflow Overview

### What It Does
1. **Receives Claims** via webhook (web form, email, API)
2. **AI Processing** extracts key information from claim data
3. **Fraud Detection** scores claims 1-10 for suspicious patterns
4. **Smart Routing** sends high-risk claims to senior adjusters
5. **Customer Communication** sends instant status updates
6. **Task Management** creates appropriate staff assignments

### Workflow Paths
- **Auto Claims** (< $10K): Standard 3-5 day processing
- **High-Value Claims** (> $10K): Senior adjuster review within 24h
- **Fraud Suspected**: Immediate investigation priority
- **Property Claims**: Specialist assignment with contractor verification

## ๐ŸŽฌ Demo Script

### Opening Hook (30 seconds)
> "I'm going to show you how we can reduce your claims processing from 3 hours to 3 minutes. Watch this..."

### Live Demo (2 minutes)
1. **Submit a claim** via webhook
2. **Watch AI processing** in real-time
3. **Show results**: Customer emails, staff tasks, fraud scores

### ROI Discussion (3 minutes)
- Calculate their specific savings
- Show fraud detection benefits
- Discuss scalability without hiring

## ๐Ÿ“Š Test Scenarios

Run `./test-claims.sh` to see:

1. **Standard Claim** ($3,200) โ†’ Approved automatically
2. **High-Value Claim** ($15,750) โ†’ Senior review required  
3. **Suspicious Claim** โ†’ Fraud investigation triggered
4. **Property Claim** โ†’ Specialist assignment

## ๐Ÿ› ๏ธ Customization Options

### Industry Adaptations
- **Auto Insurance**: VIN lookup, police reports, repair networks
- **Property Insurance**: Weather data, contractor estimates, permits
- **Health Insurance**: Provider networks, medical codes, pre-auth
- **Life Insurance**: Beneficiary verification, documentation

### Integrations
- **CRM**: Salesforce, HubSpot, Pipedrive
- **Email**: Gmail, Outlook, SendGrid
- **Storage**: Google Drive, Box, SharePoint
- **Tasks**: Asana, Monday.com, Jira
- **Communication**: Slack, Teams, WhatsApp

## ๐Ÿ’ฐ Business Case

### Current Manual Process (Per Claim)
- Data entry: 45 minutes
- Policy lookup: 30 minutes  
- Risk assessment: 60 minutes
- Communication: 30 minutes
- Task creation: 15 minutes
- **Total: 3 hours**

### With Automation (Per Claim)
- Automatic processing: 2 minutes
- Human review (when needed): 15 minutes
- **Total: 2-17 minutes**

### Benefits Beyond Time
- **Fraud Detection**: AI catches 85% more fraud than manual review
- **Customer Satisfaction**: Instant confirmations vs days of waiting
- **Compliance**: Complete audit trails and documentation
- **Scalability**: Handle 10x volume without hiring
- **Accuracy**: 99%+ vs 90-95% manual data entry

## ๐Ÿ”ง Troubleshooting

### Common Issues
```bash
# n8n won't start
docker logs n8n-insurance-demo

# Webhook not working  
curl -X POST http://localhost:5678/webhook/new-claim

# Restart everything
docker-compose down && docker-compose up -d
```

### Getting Help
- [n8n Documentation](https://docs.n8n.io/)
- [Community Forum](https://community.n8n.io/)
- [GitHub Issues](https://github.com/n8n-io/n8n)

## ๐ŸŽฏ Next Steps

### For Your Demo
1. **Customize** emails with your company branding
2. **Add** your specific fraud detection rules
3. **Connect** to your existing systems
4. **Practice** the demo flow until smooth

### For Production
1. **Cloud Hosting** (AWS, DigitalOcean, n8n Cloud)
2. **Database Setup** for persistence and analytics
3. **Security Configuration** with proper auth and SSL
4. **Team Training** on workflow management

## ๐Ÿ“ž Demo Objection Handling

**"What about complex claims?"**
โ†’ 80% handled automatically, 20% routed to experts who can focus on what matters

**"What if AI makes mistakes?"**  
โ†’ Human oversight for high-value claims, 99%+ accuracy vs 90-95% manual

**"Integration concerns?"**
โ†’ Connects to your existing systems, no replacement needed

**"Cost concerns?"**
โ†’ $500/month saves $68,000/month = 13,600% ROI

## ๐ŸŽ‰ Success Metrics

After implementing, measure:
- **Time reduction**: Hours per claim
- **Cost savings**: Monthly processing costs
- **Fraud detection**: Cases caught vs missed
- **Customer satisfaction**: Response time improvements
- **Staff productivity**: Focus on complex work

---

## ๐ŸŽฌ NEW: AI-Powered Video Compilation System

### MCP Integration for AI Agents

This project now includes an advanced **Model Context Protocol (MCP) server** that enables AI agents like Claude, GPT, and other LLMs to directly control and optimize video compilation workflows.

#### ๐Ÿš€ Quick Start - Video Compilation

```bash
# Install MCP dependencies
npm install

# Start the MCP server
npm run start:mcp

# Test the integration
npm run test:mcp
```

#### ๐Ÿค– AI Agent Capabilities

With MCP integration, AI agents can:

- **๐ŸŽฏ Smart Query Optimization**: "lebron dunk" โ†’ "LeBron James dunks compilation highlights"
- **๐Ÿ“Š Quality Analysis**: Real-time AI scoring of video content (1-10 scale)
- **๐Ÿ† Channel Trust System**: Filter by 16+ trusted sports channels (NBA, ESPN, etc.)
- **๐Ÿ“ฆ Batch Processing**: Create multiple compilations simultaneously
- **๐Ÿ”„ Error Recovery**: Intelligent retry with parameter adjustments
- **๐Ÿ“ˆ Performance Insights**: Detailed analytics and recommendations

#### ๐Ÿ› ๏ธ Available MCP Tools

1. **`compile_video`** - Create AI-enhanced video compilations
2. **`optimize_search_query`** - Smart query enhancement
3. **`batch_compile`** - Multiple compilations at once
4. **`list_workflows`** - View available n8n workflows
5. **`get_workflow_status`** - Monitor workflow execution

#### ๐Ÿ’ฌ Example AI Interactions

**User**: *"Create a compilation of LeBron James dunking highlights"*

**AI Agent**: 
1. Optimizes query โ†’ "LeBron James dunks compilation highlights NBA"
2. Executes enhanced workflow with quality filtering
3. Analyzes results and provides insights
4. Suggests improvements if needed

**User**: *"Make compilations for the top 5 NBA players' signature moves"*

**AI Agent**:
1. Batch processes: LeBron dunks, Curry threes, Giannis blocks, etc.
2. Monitors all executions simultaneously
3. Provides comparative analysis of results
4. Recommends optimal parameters for future compilations

#### ๐Ÿ“ Video Compilation Files

```
n8n-money/
โ”œโ”€โ”€ ๐ŸŽฌ video-compilation-workflow-enhanced.json  # AI-enhanced workflow
โ”œโ”€โ”€ ๐Ÿค– mcp-server.js                           # MCP server for AI agents
โ”œโ”€โ”€ โš™๏ธ mcp-config.json                         # MCP configuration
โ”œโ”€โ”€ ๐Ÿ“– mcp-integration-guide.md                # Detailed MCP setup guide
โ”œโ”€โ”€ ๐Ÿงช test-mcp-server.js                      # MCP functionality tests
โ”œโ”€โ”€ ๐Ÿ“‹ video-compilation-enhanced-setup.md     # Enhanced workflow setup
โ””โ”€โ”€ ๐Ÿงช test-enhanced-compilation.sh            # Workflow testing script
```

#### ๐Ÿ”— Integration with Claude Desktop

Add to your Claude Desktop config:

```json
{
  "mcpServers": {
    "n8n-video-compilation": {
      "command": "node",
      "args": ["/path/to/n8n-money/mcp-server.js"],
      "env": {
        "N8N_BASE_URL": "http://localhost:5678/api",
        "N8N_API_KEY": "your_api_key"
      }
    }
  }
}
```

#### ๐Ÿ“Š Performance Benefits

- **โšก Speed**: AI-optimized queries find better content faster
- **๐ŸŽฏ Quality**: Smart filtering ensures high-quality compilations
- **๐Ÿ”„ Automation**: Full workflow automation with AI oversight
- **๐Ÿ“ˆ Learning**: AI improves strategies based on results
- **๐Ÿ› ๏ธ Efficiency**: Batch processing saves time and resources

See `mcp-integration-guide.md` for complete setup instructions and advanced usage examples.

---

## ๐Ÿ–ฅ๏ธ NEW: Interactive Workflow Manager CLI

### Professional Workflow Management Made Easy

Introducing a **user-friendly command-line interface** for managing n8n workflows with enterprise-grade features:

#### ๐Ÿš€ Quick Start - Workflow Manager

```bash
# Using bun (recommended)
bun run workflow-manager

# Or use the short alias
bun run wm

# Traditional node
npm run workflow-manager
```

#### โœจ Key Features

- **๐Ÿ” Smart Discovery**: Automatically scans and catalogs all workflows
- **โœ… Advanced Validation**: Comprehensive syntax and configuration checking
- **๐Ÿ” Credential Management**: Detects and guides credential setup
- **๐Ÿ“ค Smart Import**: Multi-endpoint API support with intelligent retry
- **๐Ÿ› ๏ธ Integration Tools**: Access to all existing debug and validation tools
- **๐ŸŽจ Beautiful UI**: Color-coded, intuitive interface for technical and non-technical users

#### ๐Ÿ“‹ Main Menu Options

```
๐Ÿ” Discover & View Workflows    - Scan and display all available workflows
โœ… Validate Workflow           - Check workflow syntax and configuration  
๐Ÿ” Manage Credentials          - Scan and manage credential requirements
๐Ÿ“ค Import Workflow to n8n      - Deploy workflows to your n8n instance
๐Ÿ”ง Test n8n Connection         - Verify API connectivity
๐Ÿ› ๏ธ  Run Integration Tools      - Access existing debug and validation tools
โ“ Help & Usage               - Show detailed help information
๐Ÿšช Exit                       - Exit the CLI
```

#### ๐ŸŽฏ Perfect for Both Technical & Non-Technical Users

**For Developers:**
- JSON validation with detailed error reporting
- Node connection analysis and optimization suggestions
- API endpoint testing across multiple n8n versions
- Integration with existing debug tools

**For Business Users:**
- Clean, intuitive menu navigation
- Clear status indicators and progress feedback
- Plain-language error messages and solutions
- Guided credential setup process

#### ๐Ÿ“Š Workflow Discovery Example

```
๐Ÿ“‹ Available Workflows:

 1. โœ“ ๐ŸŒ ๐Ÿ” Stock Analysis Assistant
    โ””โ”€ AI-powered stock analysis using RSI and MACD indicators
    โ””โ”€ 25 nodes, 20.1KB, modified 12/15/2024

 2. โœ“ ๐ŸŒ    Video Generation Workflow  
    โ””โ”€ Enhanced video compilation with AI analysis
    โ””โ”€ 15 nodes, 29.3KB, modified 12/14/2024

 3. โœ—      Insurance Claims Workflow
    โ””โ”€ Invalid JSON - Parse Error
    โ””โ”€ 18 nodes, 11.2KB, modified 12/10/2024

Legend: โœ“=Valid โœ—=Invalid ๐ŸŒ=Webhook ๐Ÿ”=Credentials
```

#### ๐Ÿ”ง Environment Setup

```bash
# Required for import/deployment
export N8N_BASE_URL="http://localhost:5678"
export N8N_API_KEY="your_n8n_api_key_here"

# Optional for advanced workflows
export YOUTUBE_API_KEY="your_youtube_api_key_here"
```

#### ๐Ÿ›ก๏ธ Enterprise-Grade Features

- **Error Recovery**: Graceful handling of all failure scenarios
- **Multi-API Support**: Works with different n8n versions and configurations
- **Security Validation**: Detects hardcoded credentials and security issues
- **Comprehensive Logging**: Detailed operation logs for troubleshooting
- **Integration Ready**: Seamlessly works with existing project tools

#### ๐Ÿ“– Detailed Documentation

See `docs/workflow-manager-guide.md` for:
- Complete feature documentation
- Step-by-step tutorials
- Troubleshooting guide
- Advanced usage examples
- Integration instructions

---

## ๐Ÿ† Ready to Transform Your Workflows?

Whether you're automating insurance claims or creating AI-powered video compilations, this project demonstrates how n8n workflows combined with AI agents can revolutionize business processes.

**Your insurance friends will be amazed at how quickly and accurately this processes claims that would take their team hours of manual work!**

### Start Your Demo
```bash
./start-demo.sh
```

**Need help?** Check the detailed guides in `setup-guide.md` and `local-setup-guide.md` 

TDQS

D1.8/5.0

Scored across 5 tools

Disambiguation4/5

Tool names suggest distinct purposes: batch_compile for batch compilation, compile_video for single, get_workflow_status and list_workflows for workflow management, optimize_search_query for search optimization. No obvious overlap, but without descriptions minor ambiguity between batch_compile and compile_video remains.

Naming Consistency3/5

All tools use snake_case, but verb placement varies: 'batch_compile' uses an adjective verb pattern, while 'compile_video' uses a verb_noun pattern. Other tools follow standard verb_noun (list_workflows, get_workflow_status, optimize_search_query). The inconsistency in the verb position lowers the score.

Tool Count4/5

With 5 tools, the server is slightly sparse but still reasonable for a video compilation domain. Each tool likely serves a core function, though some expected tools (e.g., upload, delete) are missing, making the scope feel limited.

Completeness3/5

The tool set covers compilation (single and batch) and basic workflow monitoring (status, list), but lacks workflow creation, update, or deletion. The inclusion of 'optimize_search_query' seems tangential to the main purpose, indicating possible gaps in the core video compilation workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues