How to Use the Nord Pool MCP in Google ADK

Q: How does Google ADK authenticate with the Nord Pool MCP Server?

You pass the Vinkius HTTP endpoint to StreamableHttpServerParameters in your Python script. Vinkius manages the underlying API credentials, so your Google ADK agent only needs one secure token to access the market data.

Q: Can I restrict which Nord Pool tools are exposed to my Google ADK agent?

Yes, you can use the toolnames filter in your McpToolset configuration to expose only specific tools like getdayaheadprices. This keeps your Google ADK agent focused and prevents it from calling unnecessary endpoints.

Connect Gemini models to European energy markets using Google ADK to analyze Nord Pool prices and grid capacities.

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Connect Nord Pool MCP to Google ADK

Create your Vinkius account to connect Nord Pool 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 Nord Pool with Google ADK

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Feed Nord Pool data into BigQuery using Google ADK

The `get_day_ahead_prices` tool retrieves hourly European spot prices directly into your Google ADK agent using this MCP Server for real-time analysis. Your agent queries zone-specific rates and pipes them straight into BigQuery tables to update your historical pricing models. By combining these prices with historical data from `get_yearly_prices`, your Google ADK workflow builds long-term trend lines. This lets your Gemini models analyze multi-year market shifts using its massive context window without hitting API rate limits.

Track physical cross-border power flows

The `get_auction_flows` and `get_scheduled_physical_flows` tools provide the exact scheduled and physical cross-border energy exchanges for your Google ADK agents. Your agent monitors these metrics to identify physical supply movements between bidding zones like DK1 and DE-LU. Your Gemini-powered agent uses these flows alongside `get_flow_based_constraints` to model grid bottlenecks on Vertex AI. This ensures your automated trading strategies account for actual physical grid realities rather than just theoretical commercial limits.

Predict grid load and clearing volumes

The `get_consumption_forecasts` tool delivers expected load profiles that your Google ADK agent uses to identify market imbalances. Your agent compares these forecasts with cleared volumes from `get_auction_volumes` to spot zones where demand is outstripping supply. To verify API access before querying, your agent runs `get_user_subscriptions` to confirm which market data products are active. This prevents runtime failures when your Google ADK pipeline executes automated trading logic via the MCP.

Setup guide

Set up Nord Pool 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 Nord Pool 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="Nord Pool_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Nord Pool tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Nord Pool. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Nord Pool MCP in Google ADK

Your Gemini agent uses its large context window to process years of historical data from `get_yearly_volumes` and `get_yearly_prices` in a single prompt. This allows Google ADK to spot macro energy trends that shorter-context models miss.

You pass the Vinkius HTTP endpoint to `StreamableHttpServerParameters` in your Python script. Vinkius manages the underlying API credentials, so your Google ADK agent only needs one secure token to access the market data.

Yes, because the server is hosted in a secure Vinkius sandbox, your Google ADK agent connects to it via standard HTTP transport. This eliminates the need to manage complex local Docker containers or node processes on your cloud instances.

Yes, you can use the `tool_names` filter in your `McpToolset` configuration to expose only specific tools like `get_day_ahead_prices`. This keeps your Google ADK agent focused and prevents it from calling unnecessary endpoints.

The server runs in an isolated V8 sandbox that only handles public market data like `get_flow_based_constraints` and transmission capacities. No proprietary trading algorithms or internal position data are sent to the external Nord Pool API.

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