README-diagnostic-config.md

Diagnostic Configuration System

Overview

The Jenkins MCP server now uses a configurable diagnostic parameters system to eliminate hard-coded values in the diagnose_build_failure tool. All diagnostic behavior can now be customized through the diagnostic-parameters.yml configuration file.

📚 Documentation

• Complete Parameter Guide - Comprehensive documentation with examples and real-world configurations
• Quick Reference - Condensed reference for common parameters and quick fixes

Configuration File Location

• Primary: /config/diagnostic-parameters.yml
• Module: jenkins_mcp_enterprise/diagnostic_config/

Key Configuration Sections

Semantic Search

• Search query patterns for failure analysis
• Result limits and scoring thresholds
• Content preview lengths

Pattern Recognition

• Failure pattern detection rules
• Fallback analysis parameters
• Pattern matching limits

Advanced Regex Patterns

• Regex capture groups for data extraction
• Dynamic message templates with interpolation
• Named and numbered group support
• Performance-optimized pattern compilation

Recommendations Engine

• Pattern-based recommendation mappings with smart data extraction
• Priority job identification
• Investigation guidance text
• Template-based dynamic message generation

Build Processing

• Parallel processing limits
• Chunk analysis parameters
• Token management

Display and Formatting

• Hierarchy visualization settings
• Status formatting rules
• Content truncation rules

Usage

Default Configuration (Bundled)

The diagnostic parameters are automatically loaded from the bundled configuration:

from jenkins_mcp_enterprise.diagnostic_config import get_diagnostic_config

config = get_diagnostic_config()
search_queries = config.get_semantic_search_queries()
failure_patterns = config.get_failure_patterns()
recommendations = config.get_pattern_recommendations()

Custom Configuration

Method 1: Environment Variable

export JENKINS_MCP_DIAGNOSTIC_CONFIG="/path/to/custom-diagnostic-parameters.yml"
python3 -m jenkins_mcp_enterprise.server

Method 2: Command Line Argument

python3 -m jenkins_mcp_enterprise.server --diagnostic-config /path/to/custom-diagnostic-parameters.yml

Method 3: User Override Directory

Place your custom diagnostic-parameters.yml in the project's config/ directory to automatically override the bundled defaults.

Benefits

1. Flexibility: All diagnostic behavior is now configurable
2. Maintainability: No more hard-coded values scattered through the code
3. Customization: Different environments can use different diagnostic parameters
4. Hot-reload: Configuration can be reloaded without restart
5. Extensibility: Easy to add new configuration parameters

Migration

All hard-coded values from the original diagnose_build_failure tool have been extracted to the YAML configuration:

• Semantic search queries (9 patterns)
• Failure pattern recognition (7 patterns)
• Recommendation mappings (6 categories)
• Regex pattern support with capture groups and message templates
• Processing limits and thresholds
• Display formatting rules
• Investigation guidance text

New Regex Pattern Features

The system now supports advanced regex patterns for automated data extraction:

• Named Capture Groups: Extract specific data using (?P<name>pattern) syntax
• Message Templates: Dynamic message generation with {captured_group} placeholders
• Backward Compatibility: Existing string patterns continue to work unchanged
• Performance Optimization: Compiled regex patterns are cached for efficiency
• Error Handling: Invalid patterns are logged but don't break the system

Configuration Hot-Reload

from jenkins_mcp_enterprise.diagnostic_config import reload_diagnostic_config
reload_diagnostic_config()  # Reload without server restart

Next Steps

1. Start with the Quick Reference for immediate configuration needs
2. Read the Complete Guide for detailed parameter explanations and examples
3. Customize your configuration based on your technology stack and environment
4. Test changes in a development environment before deploying to production

Support

For questions about configuration parameters or troubleshooting, refer to the comprehensive documentation or check the debugging section in the complete guide.