[Technical Analysis & Implementation Plan]

Current State Assessment

graph TD
    A[Technical Core] -->|MCP Integration| B[Database Layer]
    A -->|NLP Pipeline| C[Text Processing]
    A -->|Logging| D[Infrastructure]
    B --> E[db_utils.py]
    C --> F[text_processor.py]
    C --> G[enhanced_preprocessor.py]
    D --> H[preprocessing_logger.py]

Component Analysis

1. Core Infrastructure Files

# Current Critical Files
/scripts/utils/
    ├── db_utils.py          # MCP database operations
    └── preprocessing_logger.py # Logging system

/scripts/pipeline/
    ├── text_processor.py    # Core NLP functionality
    └── enhanced_preprocessor.py # Advanced features

2. File-Specific Analysis

Database Layer (db_utils.py):

# Current Implementation
class DatabaseUtils:
    def __init__(self, db_path):
        self.db_path = db_path
        self.logger = PreprocessingLogger()

# Recommended Enhancement
class DatabaseUtils:
    """MCP-integrated database operations"""
    def __init__(self, db_path):
        self.db_path = db_path
        self.logger = CentralizedLogger.get_logger('database')
        self.connect_mcp()

NLP Pipeline (text_processor.py):

# Core Processing Chain
1. Text Ingestion → 2. Feature Extraction → 3. Metrics Computation

# Integration Points
- MCP Database Access
- Centralized Logging
- Performance Monitoring

Implementation Strategy

1. Standardization Phase:
   • Implement consistent logging across all components
   • Standardize MCP database access patterns
   • Normalize error handling
2. Integration Phase:
   • Connect components through MCP
   • Implement centralized logging
   • Create unified metrics collection
3. Documentation Phase:
   • Update technical documentation
   • Create process documentation
   • Document MCP integration points