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>
- Add PathValidator class for preventing path traversal attacks
- Add SecureSubprocessRunner for safe command execution
- Replace unsafe XML parsing with defusedxml for security
- Add comprehensive input validation tools for circuit generation
- Include security dependencies (defusedxml, bandit) in pyproject.toml
- Add security scanning job to CI/CD pipeline
- Add comprehensive test coverage for security utilities
- Add timeout constants for safe operation limits
- Add boundary validation for component positioning
This establishes a strong security foundation for the KiCad MCP server
by implementing defense-in-depth security measures across all input
vectors and external process interactions.
🤖 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.
Implement proper context management in the KiCad MCP server:
Add dedicated context.py with typed KiCadAppContext class
Convert tools to access context instead of parameters
Implement caching for thumbnails
Add proper cleanup of resources on shutdown
Improve error handling with cancellation support
Implements a more reliable PCB thumbnail generation feature using two methods:
- Primary: pcbnew Python module for high-quality rendering
- Fallback: pcbnew_cli for environments without Python modules
Adds detailed progress reporting and comprehensive error handling.
Includes documentation in docs/thumbnail_guide.md.
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.
