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Vinkius

Engineering Compliance Prover Connector for AI agents.

1 live capability

Validate structural designs against US building codes with rigorous math.

Live agent request Engineering Compliance Prover / Connector

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Why people use Engineering Compliance Prover

Engineering Compliance Prover: Ending Plausible Engineering Designs

With this Connector, the process flips. Your AI client is forced to act like a rigorous reviewer. It can't move forward until it has cited a specific code, calculated the capacity-demand ratios, and identified the controlling failure mode. You get a design that is actually ready for a peer review, not just a first draft that needs a total overhaul.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

Your AI stops guessing and starts providing code-compliant engineering calculations.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Retaining Wall Safety Check

    A user asks for a 10ft retaining wall.

  2. Real-world use case 02

    Steel Beam Capacity Analysis

    The agent calculates the capacity-demand ratio for a 20ft span under 50 psf live load using AISC 360-16.

  3. Real-world use case 03

    Electrical Circuit Validation

    The agent flags a failure to analyze voltage drop and thermal runaway in a 30A circuit for a 100ft run.

Complete set · 1capability

The complete Engineering Compliance Prover capability set.

These are the exact actions your AI can choose when you ask it to work with Engineering Compliance Prover.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Engineering Compliance Prover.

  1. 01 Capability

    Validate engineering compliance

    Forces the AI to provide a full analysis including code citations, load paths, and safety factors. It ensures every design conclusion is backed by specific math rather than vague generalities.

Set up in minutes

One URL. Then ask Engineering Compliance Prover to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Engineering Compliance Prover from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_WX6gmq5KCujIVI15RlJVQQniTOnVLSPvvQJbaqnN/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Engineering Compliance Prover, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Engineering Compliance Prover for the conversation.

Where the request belongs

Work Engineering Compliance Prover can move forward.

Built around the request

Structural engineers who need to double-check AI-generated designs for code compliance. Civil engineers ensuring load paths are properly traced in complex systems. Construction managers looking for rigorous FMEA analysis before breaking ground.

01

Structural Engineer

Verifies that a beam's capacity-demand ratio actually meets AISC 360-16 requirements on a Tuesday afternoon.

02

Civil Engineer

Ensures seismic and wind loads are correctly traced through a foundation in a complex site plan.

03

Building Inspector

Checks that material specifications and fire ratings meet local NEC and ACI codes during a review.

Build the capability set

Each Connector adds new actions and data without changing how you work.

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Bring your own AI

Change the model, client or framework. Keep Engineering Compliance Prover connected.

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Before you connect

Questions about Engineering Compliance Prover.

The practical details behind the request, access and result.

Can the Engineering Compliance Prover check for US building codes?

Yes, it validates designs against major US standards including ASCE, ACI, AISC, and NEC to ensure your projects meet legal safety requirements.

How does this Connector help with structural safety?

It forces your AI to perform rigorous failure mode analysis and calculate actual capacity-demand ratios rather than just guessing.

Does this capability work for electrical engineering?

Yes, it can check electrical designs against NEC codes, specifically looking for critical issues like voltage drop and thermal runaway.

Will it help me get my designs approved by inspectors?

It provides the exact code citations and mathematical proofs that building inspectors require to sign off on structural plans.

Can I use this to check specific material grades?

Yes, it demands precise material specifications like ASTM grades and concrete psi ratings, moving beyond vague descriptions like 'steel'.

What happens if the AI gives a vague answer?

The Connector will reject the answer and prompt the AI to provide the specific code sections and math needed to satisfy the compliance check.

Can this Connector run FEA simulations or structural math?

No. This is a strictly stateless reasoning gatekeeper. It does not perform mathematical structural analysis or run simulations. It validates the structural logic of the AI's engineering reasoning based on the inputs provided, ensuring no assumptions are skipped.

Why did the Prover reject my design with CODE_COMPLIANCE_BLIND?

Because the reasoning relied on vague appeals like 'industry standards' or 'standard engineering practice'. To pass the Prover, you must cite specific US codes (e.g., ASCE 7-22, AISC 360-16) and applicable sections.

What happens if I omit material grades?

The Prover will reject the design with TOLERANCE_OMITTED. In engineering, 'steel' or 'concrete' is not a specification. You must specify exact grades like 'ASTM A992' or '4000 psi compressive strength'.

Can this MCP run FEA simulations or structural math?

No. This is a strictly stateless reasoning gatekeeper. It does not perform mathematical structural analysis or run simulations. It validates the structural logic of the AI's engineering reasoning based on the inputs provided, ensuring no assumptions are skipped.

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