How to Use the EIA Electricity — Power Grid Intelligence MCP in Google ADK

Q: Can I restrict which tools from this MCP Server my agent sees?

You can. Use the toolnames filter in the toolset configuration to expose only specific functions, like hiding the generator inventory if you only need grid demand metrics.

Connect Gemini to U.S. power grid data using Google ADK and this MCP Server.

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Connect EIA Electricity — Power Grid Intelligence MCP to Google ADK

Create your Vinkius account to connect EIA Electricity — Power Grid Intelligence to Google ADK 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 Google ADK

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Perplexity

Process state electricity profiles

The `get_state_electricity_profiles` tool fetches massive text blocks detailing regional energy mixes. Gemini's million-token context window swallows this data whole without truncating the details. Your Google ADK setup cross-references these profiles against historical weather patterns stored in BigQuery. The agent reads the raw profile and immediately outputs a structured risk assessment for grid stability.

Track generation by fuel source

The `get_power_generation` tool isolates electric power output by state, sector, and fuel type. You use this to track exactly how quickly a region transitions from coal to renewables. Passing this EIA-923 data into Vertex AI allows your enterprise models to spot generation trends. The MCP handles the data transfer natively, writing the findings directly to your internal dashboards.

Correlate demand and retail prices

The `get_grid_demand` tool pulls hourly load metrics from major grid operators. Agents use this to monitor physical stress on the balancing authorities during extreme weather events. When you chain this with `get_electricity_prices`, the agent models how demand spikes correlate with retail rate jumps. Google ADK manages the HTTP transport natively to keep the data pipeline clean.

Setup guide

Set up EIA Electricity — Power Grid Intelligence MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with EIA Electricity — Power Grid Intelligence tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="EIA Electricity — Power Grid Intelligence_agent",
    model="gemini-2.0-flash",
    instruction="You have access to EIA Electricity — Power Grid Intelligence tools via MCP.",
    tools=mcp_tools,
)

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Common questions about EIA Electricity — Power Grid Intelligence MCP in Google ADK

Install google-adk and initialize an McpToolset with StreamableHttpServerParameters. Pass that toolset directly to your LlmAgent instance.

You can. Use the tool_names filter in the toolset configuration to expose only specific functions, like hiding the generator inventory if you only need grid demand metrics.

Yes. The endpoint supports HTTP transport out of the box. You configure the URL in the server parameters and the framework handles the connection.

Gemini's massive context window absorbs the entire 100,000-plus generator list or multi-state demand tables without dropping tokens. It reads the whole payload before reasoning.

The server exclusively handles public energy infrastructure metrics like heat rates and net generation. Your proprietary Vertex AI models and BigQuery tables remain completely isolated from the external connection.

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