Add intelligent analysis and recommendation tools for KiCad designs:
## New AI Tools (kicad_mcp/tools/ai_tools.py)
- suggest_components_for_circuit: Smart component suggestions based on circuit analysis
- recommend_design_rules: Automated design rule recommendations for different technologies
- optimize_pcb_layout: PCB layout optimization for signal integrity, thermal, and cost
- analyze_design_completeness: Comprehensive design completeness analysis
## Enhanced Utilities
- component_utils.py: Add ComponentType enum and component classification functions
- pattern_recognition.py: Enhanced circuit pattern analysis and recommendations
- netlist_parser.py: Implement missing parse_netlist_file function for AI tools
## Key Features
- Circuit pattern recognition for power supplies, amplifiers, microcontrollers
- Technology-specific design rules (standard, HDI, RF, automotive)
- Layout optimization suggestions with implementation steps
- Component suggestion system with standard values and examples
- Design completeness scoring with actionable recommendations
## Server Integration
- Register AI tools in FastMCP server
- Integrate with existing KiCad utilities and file parsers
- Error handling and graceful fallbacks for missing data
Fixes ImportError that prevented server startup and enables advanced
AI-powered design assistance for KiCad projects.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit introduces a new circuit pattern recognition system that can
automatically identify common circuit patterns in KiCad schematics, including:
- Power supply circuits (linear regulators, switching converters)
- Amplifier circuits (op-amps, transistor amplifiers)
- Filter circuits (passive and active)
- Oscillator circuits (crystal, RC, IC-based)
- Digital interfaces (I2C, SPI, UART, USB)
- Microcontroller circuits
- Sensor interfaces
The implementation includes:
- Pattern recognition algorithms for common components
- Component value extraction and normalization utilities
- MCP tools for running pattern analysis
- MCP resources for displaying formatted results
- Comprehensive documentation
Users can easily extend the pattern recognition by adding new component
patterns or circuit recognition functions.
- Implement schematic netlist parser with S-expression parsing
- Create netlist tools for extraction and connection analysis
- Add resources for netlist and component connection reporting
- Include documentation with usage guide and troubleshooting
- Register new tools and resources in server configuration
This enables extracting component connections from KiCad schematics
and analyzing connectivity between components.
This commit implements comprehensive DRC support including:
- DRC check tool integration with both pcbnew Python module and CLI fallback
- Detailed DRC reports as resources with violation categorization
- Historical tracking of DRC results with visual trend analysis
- Comparison between current and previous DRC runs
- New prompt templates for fixing violations and custom design rules
- Full documentation in drc_guide.md
The DRC system helps users track their progress over time, focusing on the
most critical design rule violations as they improve their PCB designs.
