How to Use the EIA Electricity — Power Grid Intelligence MCP in Pydantic AI

Type-safe U.S. power grid queries using Pydantic AI and this MCP Server.

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Connect EIA Electricity — Power Grid Intelligence MCP to Pydantic AI

Create your Vinkius account to connect EIA Electricity — Power Grid Intelligence 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 Electricity — Power Grid Intelligence with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Parse generator inventory strictly

The `get_generator_inventory` tool dumps records for over 100,000 operable U.S. generators. Pydantic AI forces every single row to match your exact schema definitions at runtime. If the EIA-860 data returns a string where a megawatt float should be, the agent crashes immediately. You get a loud validation error instead of silently passing bad capacity numbers to your models.

Model retail prices safely

The `get_electricity_prices` tool extracts retail rates by state and sector. Your agent uses this to map out regional cost differences based on the raw EIA-826 surveys. When combined with `get_state_electricity_profiles`, the framework ensures all state codes and sector labels are strictly typed. You never have to worry about the LLM outputting a non-existent commercial rate.

Validate thermodynamic checks

The `get_plant_generation` tool retrieves net generation and fuel consumption for individual power plants. Your Pydantic models validate the heat rates before any trading logic runs. Agents cross-check this against `get_power_generation` to verify state-level totals. Because Pydantic AI is model-agnostic, the MCP connection remains stable whether you use Claude or a local Llama instance.

Setup guide

Set up EIA Electricity — Power Grid Intelligence 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-electricity-power-grid-intelligence-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to EIA Electricity — Power Grid Intelligence tools.",
)

result = await agent.run("List recent EIA Electricity — Power Grid Intelligence transactions")
print(result.output)

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Common questions about EIA Electricity — Power Grid Intelligence MCP in Pydantic AI

Install the pydantic-ai-slim package with the mcp extra. Create an MCPToolset pointing to your HTTP endpoint, and pass it in the toolsets array when building your Agent.

The API likely returned a field that violated your Pydantic model. This is the framework working as intended to prevent silent data corruption.

No. The MCPServerHTTP class is deprecated. Use the unified MCPToolset approach with your server URL instead.

Yes. The framework is completely model-agnostic. You can run strict validation on EIA-930 demand data using any compatible backend.

The system only processes public survey responses regarding grid demand and plant generation. It never accesses your local database credentials or proprietary Pydantic schemas.

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