# Mock Data and Qdrant Collection Enhancements
## Overview
This document describes the enhancements made to the MCP integration for better testing infrastructure and Qdrant collection visibility.
## Implemented Enhancements
### 1. Mock Data Initialization
**File**: `src/services/mock-data-loader.ts`
- **Purpose**: Provides realistic sample data for testing and demonstration
- **Trigger**: Automatically loads when `LOG_LEVEL=debug`, `NODE_ENV=development`, or `LOAD_MOCK_DATA=true`
- **Collections**: Populates both `dataproc_knowledge` and `dataproc_example_test` collections
- **Data Types**:
- **Clusters**: 3 realistic cluster configurations (ML training, analytics, dev testing)
- **Jobs**: 5 sample jobs with realistic query results and error scenarios
- **Query Results**: Includes schema, rows, and metadata for demonstration
**Sample Data Includes**:
- Machine learning cluster with Jupyter/Anaconda components
- Business analytics cluster with Hive/Presto
- Development testing cluster with Zeppelin
- Successful Hive queries with sales/customer data
- Spark processing jobs with session analytics
- Failed queries with realistic error messages
### 2. Enhanced Qdrant Collection Logging
**File**: `src/services/qdrant-connection-manager.ts`
**New Features**:
- **Dashboard URLs**: Logs clickable URLs for each collection
- Format: `http://localhost:6333/dashboard#/collections/{collection_name}`
- **Data Location Info**: Shows where Qdrant data is stored
- Docker volume information for containerized setups
- Local path guidance for native installations
- **Collection Status**: Shows which key collections exist vs. need creation
**Example Output**:
```
🎯 [QDRANT-INFO] ═══════════════════════════════════════════════════════════
🎯 [QDRANT-INFO] Qdrant Instance: http://localhost:6333
🎯 [QDRANT-INFO] Dashboard URL: http://localhost:6333/dashboard
🎯 [QDRANT-INFO] Data Location: Docker volume: qdrant_storage
🎯 [QDRANT-INFO] ═══════════════════════════════════════════════════════════
📊 [QDRANT-COLLECTIONS] Available Collections:
📁 dataproc_knowledge
🌐 Dashboard: http://localhost:6333/dashboard#/collections/dataproc_knowledge
📁 dataproc_example_test
🌐 Dashboard: http://localhost:6333/dashboard#/collections/dataproc_example_test
🎯 [QDRANT-COLLECTIONS] Key Collections Status:
✅ dataproc_knowledge: http://localhost:6333/dashboard#/collections/dataproc_knowledge
✅ dataproc_example_test: http://localhost:6333/dashboard#/collections/dataproc_example_test
```
### 3. Startup Integration
**File**: `src/index.ts`
**Changes**:
- Integrated `MockDataLoader` import and initialization
- Added conditional mock data loading during development/debug mode
- Enhanced startup logging to show collection status
- Added separate `dataproc_example_test` collection for testing
**Loading Conditions**:
```typescript
// Mock data loads when any of these conditions are true:
process.env.NODE_ENV === 'development'
process.env.LOAD_MOCK_DATA === 'true'
process.env.LOG_LEVEL === 'debug'
```
### 4. Collection Discovery Enhancement
**Enhanced Logging**:
- Shows all available collections at startup
- Provides direct dashboard links for each collection
- Indicates which collections are ready vs. need creation
- Includes data location information for debugging
## Usage
### Accessing Qdrant Dashboard
1. **Main Dashboard**: `http://localhost:6333/dashboard`
2. **Knowledge Collection**: `http://localhost:6333/dashboard#/collections/dataproc_knowledge`
3. **Test Collection**: `http://localhost:6333/dashboard#/collections/dataproc_example_test`
### Testing Mock Data
1. Start the server with debug logging:
```bash
LOG_LEVEL=debug node build/index.js
```
2. Use the `query_knowledge` tool to test:
```json
{
"query": "machine learning clusters",
"type": "clusters",
"limit": 5
}
```
3. Test job queries:
```json
{
"query": "sales data analysis",
"type": "jobs",
"limit": 3
}
```
### Data Persistence
- **Docker Setup**: Data persists in `qdrant_storage` volume
- **Local Setup**: Check Qdrant config for data directory location
- **Collections**: Auto-created on first use, persist between restarts
## Benefits
1. **Better Testing**: Realistic data for demonstrating functionality
2. **Improved Debugging**: Clear visibility into Qdrant collections and data
3. **Enhanced Developer Experience**: Direct links to dashboard for inspection
4. **Documentation**: Clear understanding of data location and persistence
## Backward Compatibility
All enhancements are backward compatible:
- Mock data loading is optional and conditional
- Enhanced logging doesn't break existing functionality
- New collections don't interfere with existing ones
- All existing MCP tools continue to work unchanged
