Build a Database Issue Tracker with AI

**Issue Title:** Build Database-Connected Issue Tracker with MCP Integration

**Description:**
Create a web-based issue tracking system with the following requirements:

**Database Schema:**
- Issues table: id, title, description, status, priority, created_at, updated_at
- Comments table: id, issue_id, content, author, created_at
- Use PostgreSQL with proper foreign keys

**Backend:**
- Node.js/Express API with endpoints for CRUD operations
- Database connection setup for PostgreSQL
- Input validation and error handling
- RESTful API design

**Frontend:**
- Simple HTML/CSS/JavaScript interface
- Forms for creating/editing issues
- Issue listing with filtering by status
- Comment system for each issue

**Technical Details:**
- Include package.json with dependencies
- Environment variable configuration
- Basic SQL migration files
- Error handling and logging

Acceptance Criteria:
- Can create, read, update, delete issues
- Can add comments to issues
- Database queries work with MCP integration
- Clean, maintainable code structure

Create PostgreSQL schema for issue tracker. Output only SQL:

1. Issues table:
   - id (primary key, auto-increment)
   - title (varchar 255, required)
   - description (text)
   - status (enum: open, in_progress, closed)
   - priority (enum: low, medium, high)
   - created_at, updated_at (timestamps)

2. Comments table:
   - id (primary key, auto-increment)
   - issue_id (foreign key to issues)
   - content (text, required)
   - author (varchar 100)
   - created_at (timestamp)

3. Include:
   - Proper indexes
   - 3 sample issues
   - 2 comments per issue

Format: CREATE statements, INSERT statements, no explanations.

I need to connect to a PostgreSQL database for my issue tracker project.

Database details:
- Host: localhost (or your database host)
- Port: 5432
- Database name: issue_tracker
- Username: [your username]
- Password: [your password]

Tables created:
- issues (id, title, description, status, priority, created_at, updated_at)
- comments (id, issue_id, content, author, created_at)

Once connected, please:
1. Verify the connection works
2. Show me all current issues
3. Test creating a new issue with title "Test MCP Integration" and description "Testing database connection through MCP"

Confirm each step works before proceeding.

Using the database connection we just established, help me improve the API endpoints from the Copilot-generated code.

For each endpoint, I need you to:
1. Test the current database state
2. Suggest optimized SQL queries
3. Provide improved error handling

Endpoints to optimize:

GET /api/issues
- Add filtering by status and priority
- Include comment count per issue
- Add pagination (limit 10 per page)

POST /api/issues  
- Validate required fields
- Auto-set created_at/updated_at
- Return full created issue

GET /api/issues/:id/comments
- Order by created_at DESC
- Include author info

Test each query against our current data before providing the final code.

Generate frontend files for issue tracker. Match this exact structure:

**index.html:**
- Issue list with status badges
- "New Issue" button
- Filter dropdown (all/open/closed)
- Click issue to view details

**styles.css:**
- Dark theme
- Status badges: green=open, blue=in_progress, gray=closed  
- Responsive grid layout
- Form styling

**script.js:**
- fetchIssues() - GET /api/issues
- createIssue(data) - POST /api/issues
- showIssueDetail(id) - shows comments
- addComment(issueId, content)

**Requirements:**
- Use fetch() for API calls
- Show loading states
- Handle errors gracefully
- No frameworks, vanilla JS only

Provide 3 separate code blocks: HTML, CSS, JS. No explanations between code blocks.