kicad-tools

Tools for AI agents to work with KiCad projects.

This project provides standalone Python tools that enable AI agents (LLMs, autonomous coding assistants, etc.) to parse, analyze, and manipulate KiCad schematic and PCB files programmatically. All tools output machine-readable JSON and require no running KiCad instance.

Why Agent-Focused?

Traditional EDA tools require GUIs and manual interaction. kicad-tools bridges the gap by providing:

• Structured data access - Parse KiCad files into clean Python objects
• Machine-readable output - All CLI commands support --format json
• Programmatic modification - Edit schematics and PCBs without a GUI
• LLM reasoning interface - Purpose-built module for LLM-driven PCB layout decisions

Whether you're building an AI assistant that reviews PCB designs, automating DRC checks in CI, or experimenting with LLM-driven routing, these tools provide the foundation.

Installation

# Base install (CPU only)
pip install kicad-tools

# With CUDA GPU acceleration (NVIDIA GPUs on Linux/Windows)
pip install kicad-tools[cuda]

# With Metal GPU acceleration (Apple Silicon Macs)
pip install kicad-tools[metal]

# With native C++ router backend
pip install kicad-tools[native]

# Everything (all optional dependencies)
pip install kicad-tools[all]

To check GPU acceleration status:

kct calibrate --show-gpu

Quick Start

Command Line (kct)

# List symbols in a schematic
kct symbols project.kicad_sch
kct symbols project.kicad_sch --format json

# Trace nets
kct nets project.kicad_sch
kct nets project.kicad_sch --net VCC

# Generate bill of materials
kct bom project.kicad_sch
kct bom project.kicad_sch --format csv --group

# Run ERC (requires kicad-cli)
kct erc project.kicad_sch
kct erc project.kicad_sch --strict

# Run DRC with manufacturer rules
kct drc board.kicad_pcb
kct drc board.kicad_pcb --mfr jlcpcb
kct drc --compare  # Compare manufacturer rules

Python API

from kicad_tools import load_schematic, Schematic

# Load and parse a schematic
doc = load_schematic("project.kicad_sch")
sch = Schematic(doc)

# Access symbols
for symbol in sch.symbols:
    print(f"{symbol.reference}: {symbol.value}")

# Access hierarchy
for sheet in sch.sheets:
    print(f"Sheet: {sheet.name}")

PCB Autorouter

from kicad_tools.router import Autorouter, DesignRules

# Configure design rules
rules = DesignRules(
    grid_resolution=0.25,  # mm
    trace_width=0.2,       # mm
    clearance=0.15,        # mm
)

# Create router and add components
router = Autorouter(width=100, height=80, rules=rules)
router.add_component("U1", pads=[...])

# Route all nets
result = router.route_all()
print(f"Routed {result.routed_nets}/{result.total_nets} nets")

LLM-Driven PCB Layout

The reasoning module enables LLMs to make strategic PCB layout decisions while tools handle geometric execution:

from kicad_tools import PCBReasoningAgent

# Load board
agent = PCBReasoningAgent.from_pcb("board.kicad_pcb")

# Reasoning loop
while not agent.is_complete():
    # Get state as prompt for LLM
    prompt = agent.get_prompt()

    # Call your LLM (OpenAI, Anthropic, local, etc.)
    command = call_llm(prompt)

    # Execute and get feedback
    result, diagnosis = agent.execute(command)

# Save result
agent.save("board_routed.kicad_pcb")

CLI usage:

# Export state for external LLM
kct reason board.kicad_pcb --export-state

# Interactive mode
kct reason board.kicad_pcb --interactive

# Auto-route priority nets
kct reason board.kicad_pcb --auto-route

See examples/llm-routing/ for complete examples.

MCP Server for AI Agents

Enable AI assistants like Claude to interact with KiCad designs via the Model Context Protocol:

# Install with MCP support
pip install "kicad-tools[mcp]"

# Run the MCP server
kct mcp serve

Configure Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "kicad-tools": {
      "command": "python",
      "args": ["-m", "kicad_tools.mcp.server"]
    }
  }
}

Available MCP tools:

• Analysis: analyze_board, get_drc_violations, measure_clearance
• Export: export_gerbers, export_bom, export_assembly
• Placement: placement_analyze, placement_suggestions
• Sessions: start_session, query_move, apply_move, commit, rollback
• Routing: route_net, route_net_auto, get_unrouted_nets
• Optimization: optimize_placement, evaluate_placement

See docs/mcp/ for complete documentation.

Circuit Blocks

Build schematics using reusable, tested circuit blocks:

from kicad_tools.schematic.models import Schematic
from kicad_tools.schematic.blocks import (
    MCUBlock, CrystalOscillator, LDOBlock, USBConnector,
    DebugHeader, I2CPullups, ResetButton
)

sch = Schematic("My STM32 Design")

# Add an MCU with bypass capacitors
mcu = MCUBlock(sch, x=150, y=100,
    part="STM32F103C8T6",
    bypass_caps=["100nF", "100nF", "100nF", "4.7uF"])

# Add crystal oscillator
xtal = CrystalOscillator(sch, x=100, y=100,
    frequency="8MHz", load_caps="20pF")

# Add power supply
ldo = LDOBlock(sch, x=50, y=100,
    input_voltage=5.0, output_voltage=3.3)

# Add USB connector with ESD protection
usb = USBConnector(sch, x=50, y=150,
    connector_type="type-c", esd_protection=True)

# Add debug header for programming
debug = DebugHeader(sch, x=200, y=100, interface="swd")

# Add I2C pull-ups
i2c = I2CPullups(sch, x=180, y=150, pullup_value="4.7k")

# Add reset button with debounce
reset = ResetButton(sch, x=120, y=50, debounce_cap="100nF")

# Connect via ports
sch.add_wire(ldo.port("VOUT"), mcu.port("VDD"))
sch.add_wire(xtal.port("OUT"), mcu.port("OSC_IN"))

sch.save()

Available blocks:

• MCUBlock: Microcontroller with bypass capacitors
• CrystalOscillator: Crystal/oscillator with load capacitors
• LDOBlock: Linear regulator with input/output capacitors
• USBConnector: USB-B/Mini/Micro/Type-C with optional ESD protection
• DebugHeader: SWD/JTAG/Tag-Connect programming headers
• I2CPullups: I2C bus pull-up resistors with optional filtering
• ResetButton: Reset switch with debounce capacitor
• BarrelJackInput/USBPowerInput/BatteryInput: Power input circuits
• LEDIndicator: Status LED with current-limiting resistor
• DecouplingCaps: Decoupling capacitor placement

See boards/04-stm32-devboard/ for a complete design example.

Project Workflow

Work with complete KiCad projects using the unified Project class:

from kicad_tools import Project

# Load a KiCad project
project = Project.load("myboard.kicad_pro")

# Cross-reference schematic to PCB
result = project.cross_reference()
print(f"Unplaced components: {result.unplaced}")

# Export manufacturing files
project.export_assembly("output/", manufacturer="jlcpcb")

Progress Callbacks

Monitor long-running operations with progress callbacks:

from kicad_tools import ProgressCallback, ProgressContext
from kicad_tools.router import Autorouter

def on_progress(progress: float, message: str, cancelable: bool) -> bool:
    print(f"{progress*100:.0f}%: {message}")
    return True  # Return False to cancel

# Use with context manager
with ProgressContext(on_progress):
    router = Autorouter(...)
    router.route_all()  # Progress reported automatically

# Or create JSON-formatted callbacks for automation
from kicad_tools import create_json_callback
callback = create_json_callback()

Parametric Footprint Generators

Create KiCad footprints programmatically with IPC-7351 naming:

from kicad_tools.library import create_soic, create_qfp, create_chip

# Generate SOIC-8 footprint
fp = create_soic(pins=8, pitch=1.27)
fp.save("SOIC-8.kicad_mod")

# Generate LQFP-48
fp = create_qfp(pins=48, pitch=0.5, body_size=7.0)
fp.save("LQFP-48.kicad_mod")

# Generate 0402 chip resistor
fp = create_chip("0402", prefix="R")
fp.save("R_0402.kicad_mod")

Available generators: create_soic, create_qfp, create_qfn, create_sot, create_chip, create_dip, create_pin_header.

Symbol Library Management

Create and edit KiCad symbol libraries programmatically:

from kicad_tools.schema.library import SymbolLibrary

# Create a new symbol library
lib = SymbolLibrary.create("myproject.kicad_sym")

# Create a symbol with pins
sym = lib.create_symbol("MyPart")
sym.add_pin("1", "VCC", "power_in", (0, 5.08))
sym.add_pin("2", "GND", "power_in", (0, -5.08))
sym.add_pin("3", "IN", "input", (-7.62, 0))
sym.add_pin("4", "OUT", "output", (7.62, 0))

# Save the library
lib.save()

# Load and edit existing library
lib = SymbolLibrary.load("existing.kicad_sym")

Pure Python DRC

Run design rule checks without requiring kicad-cli:

# Check against manufacturer rules
kct check board.kicad_pcb --mfr jlcpcb --format json

# Check with custom rules
kct check board.kicad_pcb --clearance 0.15 --trace-width 0.2

Python API:

from kicad_tools.schema.pcb import PCB
from kicad_tools.validate import DRCChecker

pcb = PCB.load("board.kicad_pcb")
checker = DRCChecker(pcb, manufacturer="jlcpcb")
results = checker.check_all()

print(results.summary())
for violation in results:
    print(f"  {violation.rule_id}: {violation.message}")

Placement Optimization

Optimize component placement using physics-based or evolutionary algorithms:

from kicad_tools.optim import PlacementOptimizer, EvolutionaryPlacementOptimizer
from kicad_tools.schema.pcb import PCB

pcb = PCB.load("board.kicad_pcb")

# Physics-based optimization (force-directed)
optimizer = PlacementOptimizer.from_pcb(pcb)
optimizer.run(iterations=1000, dt=0.01)

# Get optimized placements
for comp in optimizer.components:
    print(f"{comp.ref}: ({comp.x:.2f}, {comp.y:.2f}) @ {comp.rotation:.1f}°")

# Evolutionary optimization (genetic algorithm)
evo = EvolutionaryPlacementOptimizer.from_pcb(pcb)
best = evo.optimize(generations=100, population_size=50)

# Hybrid: evolutionary global search + physics refinement
physics_opt = evo.optimize_hybrid(generations=50)
physics_opt.write_to_pcb(pcb)
pcb.save("optimized.kicad_pcb")

CLI usage:

kct placement board.kicad_pcb --optimize --iterations 1000

Trace Optimization

Optimize routed traces for shorter paths and fewer vias:

from kicad_tools.router import TraceOptimizer
from kicad_tools.schema.pcb import PCB

pcb = PCB.load("board.kicad_pcb")
optimizer = TraceOptimizer(pcb)
optimizer.optimize()
pcb.save("optimized.kicad_pcb")

CLI usage:

kct optimize-traces board.kicad_pcb -o optimized.kicad_pcb

Datasheet Tools

Search, download, and parse component datasheets:

# Search for datasheets
kct datasheet search STM32F103C8T6

# Download a datasheet
kct datasheet download STM32F103C8T6 -o datasheets/

# Convert PDF to markdown
kct datasheet convert datasheet.pdf -o datasheet.md

# Extract pin tables
kct datasheet extract-pins datasheet.pdf

# Extract images and tables
kct datasheet extract-images datasheet.pdf -o images/
kct datasheet extract-tables datasheet.pdf

Python API:

from kicad_tools.datasheet import DatasheetManager, DatasheetParser

# Search and download
manager = DatasheetManager()
results = manager.search("STM32F103C8T6")
datasheet = manager.download(results[0])

# Parse PDF
parser = DatasheetParser("STM32F103.pdf")
markdown = parser.to_markdown()

# Extract images and tables
images = parser.extract_images()
tables = parser.extract_tables()
for table in tables:
    print(table.to_markdown())

CLI Commands

Unified CLI (kct or kicad-tools)

All commands support --format json for machine-readable output.

PCB Tools

Library Tools

Modules

Features

• Pure Python parsing - No KiCad installation needed
• Round-trip editing - Parse, modify, and save files preserving formatting
• Full S-expression support - Handles all KiCad 8.0+ file formats
• Schematic analysis - Symbols, wires, labels, hierarchy traversal
• Circuit blocks - Reusable blocks for MCU, power, USB, debug headers, I2C, reset
• PCB analysis - Footprints, nets, traces, vias, zones
• Manufacturer rules - JLCPCB, PCBWay, OSHPark, Seeed design rules
• PCB autorouter - A* pathfinding with net class awareness
• Pure Python DRC - Design rule checking without kicad-cli
• Placement optimization - Physics-based and evolutionary algorithms
• Trace optimization - Path shortening and via reduction
• Footprint generation - Parametric generators for common packages
• Symbol library creation - Programmatic symbol creation and editing
• Datasheet tools - Search, download, and PDF parsing
• Progress callbacks - Monitor and cancel long-running operations
• JSON output - Machine-readable output for automation

Requirements

• Python 3.10+
• numpy (for router module)
• KiCad 8+ (optional) - for running ERC/DRC via kicad-cli

Development

This project uses uv for fast, reproducible Python environment management.

Quick Start

# Clone repository
git clone https://github.com/rjwalters/kicad-tools.git
cd kicad-tools

# Set up development environment (installs all dev dependencies)
uv sync --extra dev

# Run tests
uv run pytest

# Run linter
uv run ruff check .

# Format code
uv run ruff format .

Available Commands

If you have pnpm installed, you can use these convenience scripts:

Direct uv Commands

# Run tests with coverage
uv run pytest --cov=kicad_tools --cov-report=term-missing

# Run benchmarks
uv run pytest tests/test_benchmarks.py --benchmark-only

# Type checking
uv run mypy src/

# Full CI check
uv run ruff format . --check && uv run ruff check . && uv run pytest

Related Projects

• Zeo — A KiCad fork with an integrated AI agent sidebar and MCP server. Takes a complementary approach: live editor manipulation via IPC vs. our offline file-based analysis and optimization.
• kipy — Python bindings for the KiCad 9.0+ IPC API. Could be used to push kicad-tools optimization results into a running KiCad instance.

License

MIT