feat: Implement CLI tool, Celery workers, and VMware collector

Complete implementation of core MVP components:

CLI Tool (src/datacenter_docs/cli.py):
- 11 commands for system management (serve, worker, init-db, generate, etc.)
- Auto-remediation policy management (enable/disable/status)
- System statistics and monitoring
- Rich formatted output with tables and panels

Celery Workers (src/datacenter_docs/workers/):
- celery_app.py with 4 specialized queues (documentation, auto_remediation, data_collection, maintenance)
- tasks.py with 8 async tasks integrated with MongoDB/Beanie
- Celery Beat scheduling (6h docs, 1h data collection, 15m metrics, 2am cleanup)
- Rate limiting (10 auto-remediation/h) and timeout configuration
- Task lifecycle signals and comprehensive logging

VMware Collector (src/datacenter_docs/collectors/):
- BaseCollector abstract class with full workflow (connect/collect/validate/store/disconnect)
- VMwareCollector for vSphere infrastructure data collection
- Collects VMs, ESXi hosts, clusters, datastores, networks with statistics
- MCP client integration with mock data fallback for development
- MongoDB storage via AuditLog and data validation

Documentation & Configuration:
- Updated README.md with CLI commands and Workers sections
- Updated TODO.md with project status (55% completion)
- Added CLAUDE.md with comprehensive project instructions
- Added Docker compose setup for development environment

Project Status:
- Completion: 50% -> 55%
- MVP Milestone: 80% complete (only Infrastructure Generator remaining)
- Estimated time to MVP: 1-2 days

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

README.md

@@ -5,7 +5,7 @@
 > AI-powered infrastructure documentation generation with autonomous problem resolution capabilities.
 
 [![Version](https://img.shields.io/badge/version-2.0.0-blue.svg)](https://github.com/yourusername/datacenter-docs)
-[![Python](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
+[![Python](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/)
 [![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)
 
 ---
@@ -85,7 +85,7 @@
 ## 🚀 Quick Start
 
 ### Prerequisites
-- Python 3.10+
+- Python 3.12+
 - Poetry 1.7+
 - Docker & Docker Compose
 - MCP Server running
@@ -141,6 +141,154 @@ kubectl apply -f deploy/kubernetes/
 
 ---
 
+## 💻 CLI Tool
+
+The system includes a comprehensive command-line tool for managing all aspects of the documentation and remediation engine.
+
+### Available Commands
+
+```bash
+# Initialize database with collections and default data
+datacenter-docs init-db
+
+# Start API server
+datacenter-docs serve                          # Production
+datacenter-docs serve --reload                 # Development with auto-reload
+
+# Start Celery worker for background tasks
+datacenter-docs worker                         # All queues (default)
+datacenter-docs worker --queue documentation   # Documentation queue only
+datacenter-docs worker --concurrency 8         # Custom concurrency
+
+# Documentation generation
+datacenter-docs generate vmware                # Generate specific section
+datacenter-docs generate-all                   # Generate all sections
+datacenter-docs list-sections                  # List available sections
+
+# System statistics and monitoring
+datacenter-docs stats                          # Last 24 hours
+datacenter-docs stats --period 7d              # Last 7 days
+
+# Auto-remediation management
+datacenter-docs remediation status             # Show all policies
+datacenter-docs remediation enable             # Enable globally
+datacenter-docs remediation disable            # Disable globally
+datacenter-docs remediation enable --category network   # Enable for category
+datacenter-docs remediation disable --category network  # Disable for category
+
+# System information
+datacenter-docs version                        # Show version info
+datacenter-docs --help                         # Show help
+```
+
+### Example Workflow
+
+```bash
+# 1. Setup database
+datacenter-docs init-db
+
+# 2. Start services
+datacenter-docs serve --reload &               # API in background
+datacenter-docs worker &                       # Worker in background
+
+# 3. Generate documentation
+datacenter-docs list-sections                  # See available sections
+datacenter-docs generate vmware                # Generate VMware docs
+datacenter-docs generate-all                   # Generate everything
+
+# 4. Monitor system
+datacenter-docs stats --period 24h             # Check statistics
+
+# 5. Enable auto-remediation for safe categories
+datacenter-docs remediation enable --category network
+datacenter-docs remediation status             # Verify
+```
+
+### Section IDs
+
+The following documentation sections are available:
+- `vmware` - VMware Infrastructure (vCenter, ESXi)
+- `kubernetes` - Kubernetes Clusters
+- `network` - Network Infrastructure (switches, routers)
+- `storage` - Storage Systems (SAN, NAS)
+- `database` - Database Servers
+- `monitoring` - Monitoring Systems (Zabbix, Prometheus)
+- `security` - Security & Compliance
+
+---
+
+## ⚙️ Background Workers (Celery)
+
+The system uses **Celery** for asynchronous task processing with **4 specialized queues** and **8 task types**.
+
+### Worker Queues
+
+1. **documentation** - Documentation generation tasks
+2. **auto_remediation** - Auto-remediation execution tasks
+3. **data_collection** - Infrastructure data collection
+4. **maintenance** - System cleanup and metrics
+
+### Available Tasks
+
+| Task | Queue | Schedule | Description |
+|------|-------|----------|-------------|
+| `generate_documentation_task` | documentation | Every 6 hours | Full documentation regeneration |
+| `generate_section_task` | documentation | On-demand | Single section generation |
+| `execute_auto_remediation_task` | auto_remediation | On-demand | Execute remediation actions (rate limit: 10/h) |
+| `process_ticket_task` | auto_remediation | On-demand | AI ticket analysis and resolution |
+| `collect_infrastructure_data_task` | data_collection | Every 1 hour | Collect infrastructure state |
+| `cleanup_old_data_task` | maintenance | Daily 2 AM | Remove old records (90 days) |
+| `update_system_metrics_task` | maintenance | Every 15 minutes | Calculate system metrics |
+
+### Worker Management
+
+```bash
+# Start worker with all queues
+datacenter-docs worker
+
+# Start worker for specific queue only
+datacenter-docs worker --queue documentation
+datacenter-docs worker --queue auto_remediation
+datacenter-docs worker --queue data_collection
+datacenter-docs worker --queue maintenance
+
+# Custom concurrency (default: 4)
+datacenter-docs worker --concurrency 8
+
+# Custom log level
+datacenter-docs worker --log-level DEBUG
+```
+
+### Celery Beat (Scheduler)
+
+The system includes **Celery Beat** for periodic task execution:
+
+```bash
+# Start beat scheduler (runs alongside worker)
+celery -A datacenter_docs.workers.celery_app beat --loglevel=INFO
+```
+
+### Monitoring with Flower
+
+Monitor Celery workers in real-time:
+
+```bash
+# Start Flower web UI (port 5555)
+celery -A datacenter_docs.workers.celery_app flower
+```
+
+Access at: http://localhost:5555
+
+### Task Configuration
+
+- **Timeout**: 1 hour hard limit, 50 minutes soft limit
+- **Retry**: Up to 3 retries for failed tasks
+- **Prefetch**: 1 task per worker (prevents overload)
+- **Max tasks per child**: 1000 (automatic worker restart)
+- **Serialization**: JSON (secure and portable)
+
+---
+
 ## 📖 Documentation
 
 ### Core Documentation