# mcp-kicad-pcb-inspector

> mcp-kicad-pcb-inspector — archimedes-market-mcp-kicad-pcb-inspector. Use this tool when you need to automate the review and analysis of KiCad PCB designs, parsing files to extract layer stackups, net listings, and footprint inventories, and surfacing DRC violations and board outline geometries for pre-fabrication sanity checks. It accepts KiCad PCB files as input and outputs detailed design information, enabling AI agents to identify potential issues and optimize design review workflows. Ideal for use in design review automation and pre-fab validation contexts.

Canonical page: https://skillsregistry.net/skills/archimedes-market-mcp-kicad-pcb-inspector  
JSON: https://api.skillsregistry.net/v1/skills/archimedes-market-mcp-kicad-pcb-inspector

## Description

Parse and analyze KiCad PCB files from AI agents. Layer stackup, net listing, footprint inventory, DRC violation surfacing, board outline geometry. Built for design review automation and pre-fab sanity checks.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/archimedes-market/mcp-kicad-pcb-inspector)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "archimedes-market-mcp-kicad-pcb-inspector"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/archimedes-market-mcp-kicad-pcb-inspector` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/archimedes-market-mcp-kicad-pcb-inspector/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt