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# Database Query Guidelines

This document outlines the guidelines for executing database queries and interacting with the database in the AI-powered interface.

## Query Execution

### SQL Query Generation
- Implemented in [postgre_mcp_server.py](mdc:postgre_mcp_server.py)
- Supports read-only SQL queries (SELECT, COUNT, GROUP BY, ORDER BY)
- Destructive operations (DELETE, UPDATE, INSERT, DROP) are not allowed
- SQL syntax validation before execution
- Query results are formatted for display

### Database Connection
- Asynchronous connection management using AsyncPG
- Connection pooling for efficient resource utilization
- Error handling for connection issues
- Secure database URL management

## Best Practices

### Query Design
- Use explicit column names instead of *
- Include LIMIT clauses to restrict result sets
- Add WHERE clauses to filter results
- Consider indexing for performance
- Format SQL with proper indentation and line breaks

### Performance Optimization
- Efficient use of connection pooling
- Asynchronous query execution
- Proper error handling and logging
- Resource cleanup after query execution

## Error Handling

### Common Issues
- Invalid SQL syntax
- Table or column not found
- Connection failures
- Query timeout
- Resource constraints

### Recovery Strategies
- Graceful error messages
- Fallback responses
- Automatic retry mechanisms
- User-friendly error explanations

## Monitoring

### Logging
- Query execution logs
- Performance metrics
- Error tracking
- Resource utilization
- Response time monitoring