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Kicad MCP Pro
MCP server for KiCad, connecting AI agents to schematic and PCB workflows, ERC/DRC validation, DFM checks, BOM analysis, and manufacturing preparation—with controlled edits and…
Install
$
npx kicad-mcp-pro --helpInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →KiCad MCP Pro
Drive KiCad schematic, PCB, DRC/ERC, DFM, and manufacturing review from any MCP-capable AI agent.
Documentation · Installation · Quick Start · Tool Reference · AI Agent Setup · AI discovery
KiCad MCP Pro is a Model Context Protocol server for KiCad EDA workflows. It exposes tools, resources, and prompts for schematic, PCB, validation, DFM, and manufacturing export automation.
The server now starts with the bounded default profile: 24 read-only review tools instead of the complete expert catalog. Use build with write mode for controlled edits, release with manufacturing mode for human-gated handoff, or expert/full only for advanced trusted clients. Current catalog counts and context-size estimates come from docs/evidence/progressive-disclosure-profile-snapshot.json; see docs/agents/progressive-disclosure.md.
Telemetry and error reporting are disabled by default. Opt-in OpenTelemetry
configuration is documented in
docs/configuration.md, and privacy rules
are documented in docs/privacy.md.
Scope and honesty
KiCad MCP Pro is a professional first-pass design and review assistant, not an
automated sign-off authority. ERC/DRC and the export pipeline drive KiCad's own
engines. The signal-integrity, power-integrity, EMC, and thermal tools are
first-order, closed-form estimates (typically ~5–10% accuracy) — fast first-pass
review, not a substitute for a 2D/3D field solver, EM/FEA simulation, or formal
sign-off. Live component sourcing uses the JLCPCB public catalog by default; Nexar,
DigiKey, and Mouser are available only when their API credentials are configured. What
fraction of KiCad's programmatic surface the server drives is tracked openly in the
capability-parity matrix. Raw tool count and
capability coverage are inventory metrics, not the headline product-quality measure. End-to-end
task outcome, mutation recovery, corruption, required DRC execution, and manufacturing
reproducibility are the outcome KPIs. The committed
native-live example evidence
intentionally reports insufficient_evidence; representative-corpus target attainment remains
separate until the qualification work in #730 is complete.
Project identity
| Field | Value |
|---|---|
| Canonical repository | oaslananka/kicad-mcp-pro |
| PyPI package | kicad-mcp-pro |
| npm wrapper | kicad-mcp-pro |
| MCP Registry name | io.github.oaslananka/kicad-mcp-pro |
| Version | 4.3.0 |
| OSS maturity report | docs/repo-maturity-report.md |
| OpenSSF evidence | docs/openssf-evidence.md |
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