How to Use the Room Proportion Checker MCP in OpenAI Agents SDK

Q: Can I use Room Proportion Checker with OpenAI Agents SDK for different room types?

Yes. The MCP uses classifyroomproportions to categorize the dimensions, giving you a specific classification (like 'well-proportioned' or 'correction required') so your agent knows what kind of advice to give.

Q: What happens if I don't provide the height for Room Proportion Checker using OpenAI Agents SDK?

No big deal. The evaluatefloorareaindex tool handles that automatically, substituting a default 2.5-meter height so your agent always gets an index score without crashing.

Check room harmony and structural compliance with your OpenAI Agents SDK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Room Proportion Checker MCP to OpenAI Agents SDK

Create your Vinkius account to connect Room Proportion Checker to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Room Proportion Checker with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Proportion Checking for OpenAI Agents SDK

Your agent needs to validate a space before construction? It runs `calculate_axis_balance_ratio` based on the room's width, length, and height. The resulting score shows exactly how harmonious the proportions are—higher scores mean better balance. This MCP Server also gives you structural guidance by running `classify_room_proportions`. Instead of just giving a number, it tells your agent if the space is fundamentally well-balanced or if major changes are needed.

Validating Space Geometry in Production

When you deploy an agent using this MCP Server, you don't get guesswork. You use `evaluate_floor_area_index` to compare surface area against ceiling height. If the height is missing from the input, it automatically uses a 2.5-meter default for the calculation. This ensures your production system never fails due to incomplete data; the agent always gets an index score telling it about spatial efficiency.

Building Multi-Step Design Flows

The real value here is chaining things together. Your agent can first check a space using `calculate_axis_balance_ratio`, then use the resulting data to run through `classify_room_proportions`. It’s perfect for automated design reviews. Since this whole system runs inside the Vinkius MCP, your guardrails handle every call. You're building something deployable, not just a test script.

Setup guide

Set up Room Proportion Checker MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Room Proportion Checker tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Room Proportion Checker tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Room Proportion Checker tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Room Proportion Checker Agent",
            instructions="You have access to Room Proportion Checker tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Room Proportion Checker. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Room Proportion Checker now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Room Proportion Checker MCP in OpenAI Agents SDK

The system takes raw dimensions (L, W, H) and runs them through specific tools. It doesn't just give a simple pass/fail; it provides a detailed score that shows exactly where the space fails to meet ergonomic or architectural standards.

Yes. The MCP uses `classify_room_proportions` to categorize the dimensions, giving you a specific classification (like 'well-proportioned' or 'correction required') so your agent knows what kind of advice to give.

No big deal. The `evaluate_floor_area_index` tool handles that automatically, substituting a default 2.5-meter height so your agent always gets an index score without crashing.

The whole process is housed in Vinkius, which means every tool call produces a cryptographically signed audit trail. You know exactly what data flowed through and when.

The server only handles physical dimensions and spatial metrics, like length, width, height, and calculated surface area indexes. It never touches personal identifiers or user names.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript