How to Use the Appliance Energy Calculator MCP in OpenAI Agents SDK

Build production-ready utility tracking agents with OpenAI Agents SDK.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Appliance Energy Calculator MCP to OpenAI Agents SDK

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

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Setup Appliance Energy Calculator with OpenAI Agents SDK

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Appliance Energy Calculator MCP

Stop guessing how much that old refrigerator costs to run. Your agent can pull exact numbers using `get_appliance_impact_summary`. It grabs the complete energy and financial footprint of any household device in one shot. You get hard data backed by OpenAI guardrails. If your AI client tries to hallucinate a utility rate, the framework catches it before execution. You track every calculation right in your dashboard.

Pinpoint Daily Power Draw

Users want to know exactly what happens when they leave the AC running all day. Feed the wattage and duty cycle into `calculate_daily_consumption`. The endpoint spits out the raw kilowatt-hours. No vague estimates exist here. Just straightforward math. You can pass that output directly to another specialized agent in your network to build custom energy reports.

Track Monthly Utility Bills

Kilowatt-hours do not mean much until you attach a dollar sign. Run those daily figures through `calculate_monthly_expenses`. It applies the local rate and returns the actual cash impact on the monthly budget. This turns a basic calculator into a financial planning tool. Your deployed agent delivers exact billing parity without writing custom pricing logic from scratch.

Setup guide

Set up Appliance Energy Calculator 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 Appliance Energy Calculator tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Appliance Energy Calculator 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="Appliance Energy Calculator Agent",
            instructions="You have access to Appliance Energy Calculator tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Appliance Energy Calculator. 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.

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Common questions about Appliance Energy Calculator MCP in OpenAI Agents SDK

Install the pip package and set up MCPServerStreamableHttp with the endpoint URL. Pass it in the mcp_servers list when initializing your agent. Set cacheToolsList to true for faster boot times.

Yes. You can build a specialized finance agent that only handles utility math. The main routing agent will pass user queries directly to it when someone asks about their electric bill.

The framework guardrails catch the failure automatically. The agent will not hallucinate a fake utility cost. You can inspect the exact error trace in the OpenAI dashboard.

No. Any model compatible with your AI client works fine. The tools auto-discover and map to the current active agent.

Yes. This endpoint only processes raw wattage inputs, duty cycles, and local utility rates. It never stores personal addresses or account numbers. The calculations happen instantly and leave no trace behind.

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