How to Use the Awattar MCP in OpenAI Agents SDK

Q: How does OpenAI Agents SDK fetch next-day prices from Awattar?

The SDK connects to the MCP Server and calls getmarketdata to retrieve the EPEX Spot hourly rates. This happens automatically once the server is declared in your agent's tool list, allowing the model to plan energy consumption for the next day.

Q: Can I format Awattar data for Home Assistant using OpenAI Agents SDK?

Yes, you use the getcurrentyaml tool to fetch pre-formatted YAML statistics. Your OpenAI Agents SDK system can parse this output directly and write it to your local Home Assistant configuration file.

Q: How do I handle the daily 14:00 CET price updates?

You schedule your agent to call getmarketdata shortly after 14:00 CET. The tool returns the new hourly rates for the following day, which your agent then uses to rebuild your appliance scheduling queue.

Fetch real-time EPEX Spot electricity prices and inject YAML stats directly into your OpenAI Agents SDK workflows to automate heavy loads.

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Connect Awattar MCP to OpenAI Agents SDK

Create your Vinkius account to connect Awattar to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Awattar with OpenAI Agents SDK

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Run smart home automations via OpenAI Agents SDK

The `get_current_yaml` tool formats the latest aWATTar pricing metrics into clean YAML blocks that fit directly into your home automation system. Your OpenAI Agents SDK workflow reads this structured text to schedule high-draw appliances like EV chargers during cheapest hours. Because OpenAI Agents SDK manages state and transitions between specialized agents, you can hand off the raw YAML to a dedicated scheduling agent. This keeps your main coordination loop clean while ensuring your devices run only when electricity rates drop.

Fetch EPEX Spot market data for next-day planning

The `get_market_data` tool pulls tomorrow's spot prices directly from the Austrian and German grids as soon as they publish at 14:00 CET/CEST. Your OpenAI Agents SDK system parses these hourly rates to build an optimized energy consumption roadmap for the upcoming 24 hours. You configure the agent to run this check once a day right after publication. The built-in tracing on the OpenAI dashboard logs every pricing payload, letting you debug exactly why an agent chose a specific hour to trigger your heat pump.

Validate energy price decisions with this MCP Server

This MCP Server exposes live pricing endpoints that your OpenAI Agents SDK can query before executing high-load operations. The SDK's built-in guardrails validate the agent's proposed action against the live `get_market_data` output before turning on any hardware. If the agent attempts to run a pool pump during a peak price spike, the guardrails intercept the command. You get a deterministic safety layer that keeps your automated home from running up huge utility bills due to agent hallucinations.

Setup guide

Set up Awattar 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 Awattar tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Common questions about Awattar MCP in OpenAI Agents SDK

The SDK connects to the MCP Server and calls `get_market_data` to retrieve the EPEX Spot hourly rates. This happens automatically once the server is declared in your agent's tool list, allowing the model to plan energy consumption for the next day.

Yes, you use the `get_current_yaml` tool to fetch pre-formatted YAML statistics. Your OpenAI Agents SDK system can parse this output directly and write it to your local Home Assistant configuration file.

Install the SDK via pip and initialize the server using the `MCPServerStreamableHttp` class with your Vinkius endpoint. Pass this server instance in the `mcp_servers` list when constructing your agent to auto-discover all tools.

You schedule your agent to call `get_market_data` shortly after 14:00 CET. The tool returns the new hourly rates for the following day, which your agent then uses to rebuild your appliance scheduling queue.

The MCP Server only retrieves public EPEX Spot pricing and generic YAML templates via `get_current_yaml` and `get_market_data`. No personal smart meter data, home addresses, or private utility accounts are ever sent to or processed by the server.

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