How to Use the EIA State Energy — U.S. Regional Energy Data MCP in Pydantic AI

Q: How do I initialize the EIA State Energy — U.S. Regional Energy Data MCP Server in Pydantic AI?

Install pydantic-ai-slimmcp. Create an MCPToolset pointing to your Vinkius HTTP endpoint, then pass it in the toolsets array to your Agent.

Type-safe U.S. energy data MCP Server for Pydantic AI agents.

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Connect EIA State Energy — U.S. Regional Energy Data MCP to Pydantic AI

Create your Vinkius account to connect EIA State Energy — U.S. Regional Energy Data to Pydantic AI 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 EIA State Energy — U.S. Regional Energy Data with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Validate state energy metrics at runtime

`get_state_energy_data` returns state-level energy production, consumption, and expenditures spanning back to 1960. You define the exact schema you expect, and Pydantic AI forces the language model to adhere to it. If the API returns a string where you expected a float for energy prices, the agent fails loudly with a validation error. You never end up with silent data corruption in your regional energy reports.

Parse national totals predictably

`get_total_energy` queries the Monthly Energy Review for U.S. total production, stocks, and CO2 emissions across all major fuel types. The agent executes the request through this MCP Server and maps the response directly into your typed data classes. Because this framework is model-agnostic, you can swap between Anthropic or local models to see which parses the national petroleum and coal metrics best. The tool execution remains identical regardless of the underlying LLM.

Catch nuclear capacity errors instantly

`get_nuclear_outages` isolates the current outage status for U.S. nuclear reactors. Your agent fetches the reactor data and validates the capacity figures at runtime using this Pydantic AI MCP Server integration. If the structure of the outage report shifts, your code catches the error immediately instead of passing hallucinated fields downstream. You get absolute certainty about the grid data entering your application.

Setup guide

Set up EIA State Energy — U.S. Regional Energy Data MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "eia-state-energy-us-regional-energy-data-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to EIA State Energy — U.S. Regional Energy Data tools.",
)

result = await agent.run("List recent EIA State Energy — U.S. Regional Energy Data transactions")
print(result.output)

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Common questions about EIA State Energy — U.S. Regional Energy Data MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Create an `MCPToolset` pointing to your Vinkius HTTP endpoint, then pass it in the `toolsets` array to your Agent.

Yes. The framework supports both Streamable HTTP and SSE transports for your MCP connection. This is crucial when pulling heavy historical datasets from 1960 to the present.

The agent throws a validation error immediately. You get strict runtime checks on all energy prices, CO2 emissions, and consumption metrics.

You certainly can. As long as your local model supports function calling, it can request U.S. totals or state-level expenditures through this integration.

We isolate your requests for state energy expenditures and nuclear outage data within a V8 sandbox. Vinkius maintains a zero-trust environment where your API calls vanish as soon as the data transfers.

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