How to Use the GridStatus MCP in OpenAI Agents SDK

Q: How does the OpenAI Agents SDK manage GridStatus API limits?

The agent calls getapiusage to read your remaining row allowance. You can set up a guardrail function in Python to block calls if your quota drops below a safe limit.

Q: Can I query historical capacity market data?

Yes. Use getcapacitydata to track long-term resource adequacy commitments. This is currently available for PJM and helps your agent evaluate future grid reliability.

Feed live US electricity grid data to your OpenAI Agents SDK with auto-discovered tools and built-in runtime guardrails.

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Connect GridStatus MCP to OpenAI Agents SDK

Create your Vinkius account to connect GridStatus 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 GridStatus with OpenAI Agents SDK

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Monitor Live Grid Load and Pricing

Your agent pulls real-time power demand across US markets. Feed this data to specialized nodes using `get_load_data` to track grid stress. This MCP server lets your agent instantly fetch 5-minute interval prices using `get_realtime_lmp`. The system tracks price spikes as they happen. If an agent detects a spike, it hands off to a trading agent to execute market actions. You see the entire execution path and tool call inside your OpenAI developer dashboard.

Clean Energy Transition Tracking via OpenAI Agents SDK

Build agents that analyze renewable generation trends across major US grids. Your agent calls `get_fuel_mix` to pull solar, wind, and fossil fuel ratios. This lets you build automated green energy reports without manual data scraping. The OpenAI Agents SDK handles tool discovery automatically when you connect this MCP Server. Your agent inspects schemas using `get_dataset_metadata` to map out exactly what columns are available before running deep queries.

Compare Regional Electricity Markets

Spot trading opportunities across different grid regions. Your agent queries multiple ISOs simultaneously using `get_standardized_data` to return uniform metrics. This removes the headache of mapping different column names from ERCOT to CAISO. For deeper analysis, your agent uses `query_dataset` to run custom filters on historical pricing. It keeps track of API limits using `get_api_usage` to prevent unexpected rate-limiting during high-frequency runs.

Setup guide

Set up GridStatus 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 GridStatus tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate GridStatus 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="GridStatus Agent",
            instructions="You have access to GridStatus 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 GridStatus MCP in OpenAI Agents SDK

Install the SDK and instantiate the HTTP server class with the Vinkius endpoint. Pass the MCP server instance directly to your agent constructor. The agent auto-discovers all twelve grid tools instantly.

Yes. Your agent queries 15-minute Settlement Point Prices using `get_realtime_spp`. It can trigger a handoff to a mitigation agent when prices exceed a specific threshold.

The agent calls `get_api_usage` to read your remaining row allowance. You can set up a guardrail function in Python to block calls if your quota drops below a safe limit.

Yes. Use `get_capacity_data` to track long-term resource adequacy commitments. This is currently available for PJM and helps your agent evaluate future grid reliability.

The MCP Server only processes public electricity grid data, including load, pricing, and fuel mix. No proprietary trading algorithms or private API keys are stored on Vinkius servers, as all requests run through isolated, ephemeral sandboxes.

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