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partreel

Open, no-login KiCad parts registry for humans & AI agents — verified footprints, symbols & 3D models (STEP/GLB) with datasheet provenance + static JSON API + MCP server

Install / Use

claude mcp add mingyo186 -- npx -y github:mingyo186/partreel

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

70/100

Supported Platforms

Claude Code
Claude Desktop

Tags

Our assessment of partreel

partreel scores 70/100 on our quality scale, 3788th of 4,632 Development & Engineering skills we index.

Its MCP Server is 3429 KB long, well organised into 21 sections with 1 code example: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
21/30
Structure
17/20
Description
15/15
Adoption
3/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 26 days ago, so partreel is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 80/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-11-07. Automated pattern scan on 2026-11-07. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

partreel compared with similar skills

All 4 of these similar skills score higher than partreel; compare them before choosing.

SkillScoreStarsUpdatedFormat
partreel (this skill)by mingyo18670326d agoMCP Server
taste-skillby Leonxlnx100111.4k2d agoCLAUDE.md
Agent-Reachby Panniantong100109.8k1d agoCLAUDE.md
headroomby headroomlabs-ai10079.1ktodayCLAUDE.md
ai-job-searchby ai-job-search-dev10070.2k1d agoCLAUDE.md

Frequently asked questions

How do I install partreel?
Run claude mcp add mingyo186 -- npx -y github:mingyo186/partreel. The install tabs above show the steps for each supported agent.
Which AI agents does partreel work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is partreel safe to use?
Our scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 80/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is partreel still maintained?
The repository was last updated 26 days ago, so partreel is actively maintained.

PartReel — open KiCad parts registry for humans & AI agents

No login. No paywall. Machine-verified. Every part ships as a bundle of KiCad footprint (.kicad_mod) + symbol (.kicad_sym) + 3D model (STEP + GLB), generated from manufacturer-datasheet dimensions and checked by automated quality gates on every deploy.

Site: https://partreel.com · API: https://partreel.com/api/ · MCP server: https://mcp.partreel.com/mcp · Agent guide: https://partreel.com/agents/

Why this exists

  • The official KiCad library is excellent — use it when it has your part. PartReel focuses on parts the official library doesn't cover (checked against GitLab master before we add anything).
  • Aggregator sites lock downloads behind sign-ups; agents and scripts can't use them. Everything here is a plain URL.
  • AI agents regenerate footprints from scratch every time — wasteful and unverified. PartReel is the place to fetch a verified part instead, and report back (field_reports in the API).

Provenance — verify us, don't trust us

Every part's API entry (/api/v1/parts/<id>.json) carries machine-readable provenance: the exact datasheet figure/table each dimension came from (dimensions_source), the generator source file in this repo, the quality gates it passed, and field-usage reports. Gates run in CI on every push and block deployment on failure — see .github/workflows/deploy.yml.

| Gate | Checks | |---|---| | validate_kicad.py | s-expression structure, pads, layers, pin-1 | | KLC drawing rules | silk 0.12 / fab 0.10 + pin-1 chamfer / courtyard 0.05 | | check_overlap.py | no overlapping text in previews | | check_render.py | files exist, SVG pads/outlines match source, pages/API present, datasheet cited | | check_zfight.py | no coplanar z-fighting faces, pins are individual bodies | | validate_step.py | STEP solids pass FreeCAD kernel isValid |

For AI agents

  • Static JSON API, no auth, no rate limit: /api/v1/parts.json
  • Remote MCP server (nothing to install): claude mcp add --transport http partreel https://mcp.partreel.com/mcp — tools: search_parts, get_part, list_parts, submit_part, report_feedback, request_part, how_to_contribute
  • Machine guide: /llms.txt
  • The loop: search → use → if a part is missing, build it from the datasheet and submit_part — it is shared with every agent instantly (labeled unverified/staging), then hourly CI gates + review promote it to verified.
  • request_part generates parametric families (pin headers, LDOs) server-side in ~5 min; the PR path (CONTRIBUTING-AGENTS.md) remains for 3D models and edits.

Repository layout

library/                 part assets (CC-BY-4.0): .kicad_mod / .kicad_sym / .step / .glb / meta.json
generators/              parametric generators (Python; KiCad text + FreeCAD 3D) + quality gates
api/, p/, assets/        static site & JSON API (built by CI)
mcp/                     Cloudflare Worker MCP server

License

  • Code (generators, site): MIT
  • Part assets (library/): CC-BY-4.0

Dimensions come from manufacturer datasheets and are provided as-is; verify before manufacturing.

Credits

Bug reports are contributions. Reporters whose feedback led to a fix are recorded in CREDITS.md and in the fix commits as Reported-by:; imported-library authors are credited in ATTRIBUTIONS.md.

Parts index

<!-- PARTS:BEGIN -->

Currently 18258 parts, all machine-verified (structure, KLC drawing rules, render completeness, 3D coplanar/merged-pin checks, STEP kernel) with datasheet-cited dimensions.

connector (4330)

| Part | MPN | Manufacturer | Files | |---|---|---|---| | 004500 (CERN library) | 004500 | ERNI | cern_erni_004500 | | 02 01 160 2101 (CERN library) | 02 01 160 2101 | HARTING | cern_harting_02_01_160_2101 | | 02 01 160 2102 (CERN library) | 02 01 160 2102 | HARTING | cern_harting_02_01_160_2102 | | 02 02 160 2201 (CERN library) | 02 02 160 2201 | HARTING | cern_harting_02_02_160_2201 | | 02 02 160 2301 (CERN library) | 02 02 160 2301 | HARTING | cern_harting_02_02_160_2301 | | 02 04 160 1101 (CERN library) | 02 04 160 1101 | HARTING | cern_harting_02_04_160_1101 | | 02 07 160 1101 (CERN library) | 02 07 160 1101 | HARTING | cern_harting_02_07_160_1101 | | 031-6575 (CERN library) | 031-6575 | AMPHENOL-RF | cern_amphenol_031_6575 | | 054392 (CERN library) | 054392 | ERNI | cern_erni_054392 | | 054546 (CERN library) | 054546 | ERNI | cern_erni_054546 | | 054594 (CERN library) | 054594 | ERNI | cern_erni_054594 | | 054595 (CERN library) | 054595 | ERNI | cern_erni_054595 | | 054596 (CERN library) | 054596 | ERNI | cern_erni_054596 | | 063197 (CERN library) | 063197 | ERNI | cern_erni_063197 | | 063209 (CERN library) | 063209 | ERNI | cern_erni_063209 | | 063210 (CERN library) | 063210 | ERNI | cern_erni_063210 | | 064317 (CERN library) | 064317 | ERNI | cern_erni_064317 | | 064318 (CERN library) | 064318 | ERNI | cern_erni_064318 | | 064321 (CERN library) | 064321 | ERNI | cern_erni_064321 | | 09 02 164 2921 (CERN library) | 09 02 164 2921 | HARTING | cern_harting_09_02_164_2921 | | 09 02 264 6825 (CERN library) | 09 02 264 6825 | HARTING | cern_harting_09_02_264_6825 | | 09 02 264 6850 (CERN library) | 09 02 264 6850 | HARTING | cern_harting_09_02_264_6850 | | 09 03 000 6104 (CERN library) | 09 03 000 6104 | HARTING | cern_harting_09_03_000_6104 | | 09 03 000 6110 (CERN library) | 09 03 000 6110 | HARTING | cern_harting_09_03_000_6110 | | 09 03 000 6162 (CERN library) | 09 03 000 6162 | HARTING | cern_harting_09_03_000_6162 | | 09 03 000 6182 (CERN library) | 09 03 000 6182 | HARTING | cern_harting_09_03_000_6182 | | 09 03 000 6225 (CERN library) | 09 03 000 6225 | HARTING | cern_harting_09_03_000_6225 | | 09 03 000 6262 (CERN library) | 09 03 000 6262 | HARTING | cern_harting_09_03_000_6262 | | 09 03 000 6265 (CERN library) | 09 03 000 6265 | HARTING | cern_harting_09_03_000_6265 | | 09 03 124 6901 (CERN library) | 09 03 124 6901 | HARTING | cern_harting_09_03_124_6901 | | 09 03 142 6901 (CERN library) | 09 03 142 6901 | HARTING | cern_harting_09_03_142_6901 | | 09 03 160 6901 (CERN library) | 09 03 160 6901 | HARTING | cern_harting_09_03_160_6901 | | 09 03 164 2921 (CERN library) | 09 03 164 2921 | HARTING | cern_harting_09_03_164_2921 | | 09 03 164 6921 (CERN library) | 09 03 164 6921 | HARTING | cern_harting_09_03_164_6921 | | 09 03 164 6922 (CERN library) | 09 03 164 6922 | HARTING | cern_harting_09_03_164_6922 | | 09 03 164 6951 (CERN library) | 09 03 164 6951 | HARTING | cern_harting_09_03_164_6951 | | 09 03 178 7901 (CERN library) | 09 03 178 7901 | HARTING | cern_harting_09_03_178_7901 | | 09 03 196 2921 (CERN library) | 09 03 196 2921 | HARTING | cern_harting_09_03_196_2921 | | 09 03 196 6921 (CERN library) | 09 03 196 6921 | HARTING | cern_harting_09_03_196_6921 | | 09 03 224 6805 (CERN library) | 09 03 224 6805 | HARTING | cern_harting_09_03_224_6805 | | 09 03 224 6830 (CERN library) | 09 03 224 6830 | HARTING | cern_harting_09_03_224_6830 | | 09 03 224 6864 (CERN library) | 09 03 224 6864 | HARTING | cern_harting_09_03_224_6864 | | 09 03 224 6864 (CERN library) | 09 03 224 6864 | HARTING | cern_harting_09_03_224_6864_a | | [09 03 232 6825 (CERN library)](https://partreel.com/p/cer

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3
CategoryDevelopment
Updated26d ago
Forks1

Languages

HTML

Trust signals

80/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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