Install
$ agentstack add mcp-almightyshui-mechanical-ai-skill ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
AI Mechanical Engineering Review Skill
Upload a STEP assembly. Understand the design. Review engineering risks. Generate reports.
> Not another CAD copilot. Mechanical AI Skill focuses on engineering understanding and review — not geometry generation. It's a structured engineering-review layer that lets an AI agent (Claude Code, Codex, Cursor) reason about a mechanical assembly. > > Put differently: it's the first AI-native engineering review layer for mechanical assemblies — not a CAD tool, not a simulation tool, not a DFM tool, but the reasoning layer that sits between an AI agent and all of those.
Upload assembly → Understand assembly → Engineering review → Engineering report
Why
Mechanical assemblies are hard for AI agents to reason about. A large STEP assembly can contain:
- Hundreds of components
- Complex mating relationships
- Hidden mechanisms
- Manufacturing risks
- Assembly complexity
Mechanical AI Skill provides a structured engineering review layer so an AI agent can go from a raw CAD file to an understanding of the design and a real engineering review — with the honest assumptions and caveats an engineer would attach. This is the open Community Edition, fully functional on its own.
What it is — and is not
Mechanical AI Skill is not:
- ❌ A CAD modeling copilot
- ❌ A generative / geometry-creation tool
- ❌ A drawing or feature-modeling assistant
Mechanical AI Skill is:
- ✅ Assembly understanding (structure, BOM, mechanisms)
- ✅ Engineering review (interference, DFM/DFA, risk)
- ✅ Mechanical diagnostics (clashes, clearances, complexity)
- ✅ Engineering reporting (PDF / HTML)
Example — one STEP in, a full review out
Input: a real 39 MB SolidWorks-exported STEP of a dual-station robotic welding cell. No SolidWorks, no geometry kernel — just the Community Edition reading the STEP. Every figure is the actual output; nothing is invented.
Output (review_summary, written to mech_review/review_summary.md next to the STEP)
EXECUTIVE SUMMARY
142 unique parts · 357 instances · assembly depth 4
COMPLEXITY
High — 357 instances, 142 unique parts, depth 4, 2 mechanism subsystems
MANUFACTURING MIX
Custom (in-house) 78% · Commercial / classified 22%
MECHANISMS
Robot Arm (95%) · Pneumatic Cylinder (76%)
VENDORS
FANUC (7) · Nook (4) · SCHUNK (3) · Bimba (3) · Banner (1) · Lincoln Electric (1)
CATEGORIES
Robot/Arm 7 · Grippers 5 · Linear Motion 4 · Pneumatic 3 · Sensors 1 · Welding 1
Custom Machined: 301065 (44) · 301066 (19) · 307070 (6) · 301060 (5) · 330001 (5)
RISK
88 / 100 (higher = lower risk)
FINDINGS
1. High part variety (Medium)
Evidence: 142 unique parts across 357 instances
Impact: Higher inventory, sourcing, and assembly complexity
Recommendation: (Professional)
2. High custom-part ratio (Medium)
Evidence: 78% of classified instances are custom (in-house)
Impact: Manufacturing cost and lead time driven by in-house parts
Recommendation: (Professional)
3. High instance count (Medium) · 357 instances · Recommendation: (Professional)
4. Deep assembly structure (Low) · depth 4 · Recommendation: (Professional)
A plain STEP viewer shows you the geometry. None of them tell you, from the file alone, that this is a dual-station FANUC M-16iB welding cell, 78% in-house parts, six vendors, high complexity, with four findings worth a closer look. That's the difference between viewing a model and understanding an assembly.
Full write-up: [Robotic Welding Cell](examples/robotweldingcell/review.md) — real 39 MB STEP, every number verbatim.
It can also emit the structure as a diagram that renders right here on GitHub:
graph TD
n1["Welding Cell"] --> n2["Station 1"]
n1["Welding Cell"] --> n3["Station 2"]
n2["Station 1"] --> n4["M-16iB Robot"]
n2["Station 1"] --> n5["Pneumatic Fixtures"]
n3["Station 2"] --> n6["M-16iB Robot"]
n3["Station 2"] --> n7["Pneumatic Fixtures"]
What the Community Edition already does
No license. Runs standalone. On a STEP file alone (no SolidWorks), it reads structure and runs approximate geometry checks; with SolidWorks it runs the production checks.
Assembly understanding
- Executive Review — one command (
review_summary) reads the STEP and returns an engineer-facing verdict: assembly scale, detected mechanisms, vendors, categories, a name-level BOM, and a risk score — you don't pre-run the other checks, it orchestrates them - BOM generation + part count + standard-part identification — works on a plain STEP with no SolidWorks and no geometry kernel: a real name-level BOM with true quantities (from assembly instance counts), honestly flagged as name-level (no volume/mass/material)
- Assembly Structure Summary — components, mates, grouping (what is there)
- Assembly tree — a clean structure tree to confirm the model parsed
- Mechanism Detection (Experimental) — gear train, timing belt, chain drive, lead screw, robot arm, linear slide, pneumatic cylinder, rotary table
- Vendor summary — detects component brands from names (FANUC, SCHUNK, SMC, THK, Banner …)
- Assembly statistics — top-level subassemblies and their instance counts
- Component category summary — counts by kind (motors, sensors, cylinders, robots …) — statistics, not a procurement list
- Exploded structure graph — a Mermaid diagram of the assembly tree (renders right in the README)
- Adjacency graph — which parts touch / are neighbours (geometric, from a STEP); without a geometry kernel it returns a clearly-labelled hierarchy graph (belongs-to, not touches) — never the two confused. The force-flow and constraint graphs are Professional
Engineering review & diagnostics
- Interference detection + clearance check (SolidWorks, or approximate from STEP)
- Rule-based DFM — deep holes, thin walls, sharp corners (on supplied feature measurements)
- Basic DFA — part/fastener counts, assembly-depth complexity, tool-clearance checks
- Fastener checks — thread-engagement (n×D rule) and missing-washer / missing-nut stack screens
- Risk score — 0–100 with a transparent breakdown (interference · DFM · DFA complexity · tool accessibility · assembly depth) — not a black-box number
Simulation (real, analytical)
- Static analysis (single load case) — stress, deflection, safety factor
- Modal analysis (first 3 modes) — natural frequencies + resonance check
Reporting
- Engineering report — any result → clean PDF / HTML with status, tables, assumptions, caveats
> The Professional Edition is the Engineering Intelligence Layer. Where the > Community Edition answers what is this assembly (structure, mechanisms, vendors, > first-pass review), Professional answers the questions an experienced engineer asks > next: > - Why does this design exist? — design-intent recognition, function identification > - How does force flow through it? — automatic load-path and power-flow reasoning > - Where will it fail in real life? — failure-mode prediction, FMEA, fatigue/thermal/CFD > - How should it be manufactured at scale? — advanced DFM/DFA, cost, procurement > > Concretely that means fatigue, thermal, CFD, multibody dynamics, topology > optimization, automatic load/constraint identification, advanced DFM/DFA, advanced > risk scoring, automated design review, and procurement intelligence. Those commands > ship here but return enterprise_required until the licensed core is installed. > Full split in [Editions](#editions).
How it compares
It isn't competing with CAD or CAE tools — it sits in a different layer (the AI agent's reasoning layer) and hands off to them where they're authoritative.
| | What it's for | Runs without a CAD/CAE seat? | Driven by an AI agent? | |---|---|---|---| | SolidWorks / CAD | model & assemble geometry | no | no | | ANSYS / Abaqus (CAE) | high-fidelity simulation | no | no | | DFM checkers | manufacturability rules | usually needs the CAD seat | no | | Mechanical AI Skill | understand & review an assembly, then route to the right tool | yes (STEP-only fallback) | yes (Claude Code / Codex / Cursor) |
The skill answers "what is this, is it sane, where should I look" in plain language from a STEP file, then points you to SolidWorks for the authoritative interference check, or to the Professional core for full FE / design review. It's the layer that was missing — not a replacement for the tools underneath it. See [benchmarks](docs/BENCHMARKS.md).
Architecture
The skill sits between your AI agent and the real CAD/CAE tools, exposing one stable JSON contract. Free capabilities compute locally; Professional capabilities delegate to the licensed core (or return enterprise_required).
Install
Claude Code (recommended — plugin, auto-updates via marketplace):
/plugin marketplace add almightyshui/Mechanical-AI-Skill
/plugin install mechanical-ai-skill
Codex, Cursor, or any Agent Skills host:
git clone https://github.com/almightyshui/Mechanical-AI-Skill
bash mechanical-ai-skill/install.sh all # Claude Code + Codex (+ Cursor in a repo)
Per agent: install.sh claude | codex | cursor. Manual paths in [INSTALL.md](INSTALL.md).
Zero config — works on a STEP file alone, however you point at it. Hand the skill a .STEP, a non-standard extension (e.g. a .snapshot.1), a .zip, or the unzipped folder — it resolves all of them and picks the right STEP. With no SolidWorks and no geometry kernel, BOM, part count, assembly tree, mechanisms, vendors, categories, the executive review, and approximate interference/clearance all run directly from the STEP (geometry-dependent checks are flagged approximate; production sign-off still uses the SolidWorks check). Every result carries a one-line headline and a status (ok / deck_only / needs_input / enterprise_required / failed) so an agent never misreads a graceful degradation as a failure — and never fabricates data the skill didn't compute. Verify in 30 seconds:
git clone https://github.com/almightyshui/Mechanical-AI-Skill
cd mechanical-ai-skill
bash examples/demo.sh # full review pass, no SolidWorks needed
It ends with a machine-readable summary an agent would report:
{
"status": "ok",
"bom_unique_parts": 27,
"interference_count": 2,
"dfm_findings": {"blocker": 0, "risk": 2},
"static_safety_factor": 5.67,
"risk_score": 71
}
What you do with it
Make a BOM / understand a model
> "Generate a BOM and summarize this assembly's structure."
Walks the SolidWorks tree → bill of materials (item, part, quantity), unique-part and total counts, standard-part flags (screws, bearings, washers). For the structure summary, it returns the component + mate structure and a plain inventory — what is there. Interpreting why it's designed that way (working principle, power flow, design intent) is the Professional Edition.
Check an assembly
> "Check this assembly for interference."
Runs SolidWorks Interference Detection → each clashing pair with its overlap volume, plus mate errors, over/under-defined mates, dangling references, and clearance violations. Distinguishes a likely press-fit from a real clash. No SolidWorks on this machine? You get a macro to run, not a fake "all clear."
Get a report
> "Put that in a PDF."
Any result — BOM or diagnostics — renders to a clean PDF (or HTML, zero-dependency fallback) with status, tables, assumptions, and caveats. Drop it into a design review.
Editions
| Capability | Community (free) | Professional | |---|:--:|:--:| | BOM · part count · standard-part ID · assembly structure summary | ✅ | ✅ | | Interference · mate · clearance diagnostics | ✅ | ✅ | | STEP export · basic PDF/HTML report | ✅ | ✅ | | Static analysis | single load case | multi-load, contact, nonlinear, auto-faces | | Modal analysis | first 3 modes | unlimited modes, prestressed | | DFM | rule-based (supplied features) | advanced rule library | | DFA | basic (complexity, tool clearance) | sequence, path, time, automation | | Mechanism / vendor detection | type & brand ID | design intent, sourcing, alternates | | Risk score | simple roll-up | criticality-weighted, code-aware | | Fatigue · thermal · CFD · multibody dynamics | — | ✅ | | Topology optimization / lightweighting | — | ✅ | | Automatic load / constraint / mesh identification | — | ✅ | | Automated design review · procurement · advanced report | — | ✅ |
Community commands for Professional capabilities exist and validate your task, but return enterprise_required with an upgrade note — they never crash and never fabricate output. Installing the licensed mechanical_ai_core package lights them up through the same commands (the skill auto-detects and delegates; see [sdk/CONTRACT.md](sdk/CONTRACT.md)).
How it answers, and why you can trust it
| Status | Meaning | |--------|---------| | ok | ran, valid results | | needs_input | required data missing — agent asks you, nothing ran | | deck_only | SolidWorks not installed — macro generated + run command | | failed | ran but errored — never reported as valid | | enterprise_required | needs the Professional core — upgrade note, graceful |
Every default and auto-choice is in assumptions; every limit in caveats. Standard-part flags are name heuristics, marked for confirmation.
For builders
Open, stable JSON contract — identical across agents. See [AGENT_README.md](AGENT_README.md) and [sdk/CONTRACT.md](sdk/CONTRACT.md). Open connectors in [connectors/](connectors); task templates in [examples/](examples). Minimal example:
cat > task.json Skills run with your agent's permissions. Read [`SKILL.md`](SKILL.md) first; install only from sources you trust. This skill drives licensed CAD tools through their own APIs.
## Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- **Author:** [almightyshui](https://github.com/almightyshui)
- **Source:** [almightyshui/Mechanical-AI-Skill](https://github.com/almightyshui/Mechanical-AI-Skill)
- **License:** MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.