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How to Use the ENTSO-E MCP in Pydantic AI

Run type-safe European energy market analysis with Pydantic AI validating every ENTSO-E tool response at runtime.

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Pydantic AI

Connect ENTSO-E MCP to Pydantic AI

Create your Vinkius account to connect ENTSO-E 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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Validate wholesale energy prices in Pydantic AI

`get_day_ahead_prices` fetches wholesale electricity prices across European bidding zones directly into your type-safe agent. Pydantic AI validates the structure of the incoming XML data at runtime, throwing an immediate error if the schema deviates. To track volatility, the agent queries `get_balancing_prices` to monitor real-time grid correction costs. This MCP Server connection ensures that your automated trading algorithms never execute decisions based on corrupted or malformed pricing payloads.

Audit installed grid capacity with Pydantic AI

`get_installed_generation` retrieves the total nominal capacity of power assets across Europe by fuel type. Your Pydantic AI agent parses this data into strongly typed models, guaranteeing that solar, wind, and nuclear capacities are classified correctly. The agent then calls `get_forecasted_generation` to see how much of that capacity is scheduled to run. By enforcing strict type checks, you prevent downstream calculation errors when mapping European energy supply.

Track grid maintenance using this MCP Server

`get_transmission_outages` retrieves active and scheduled maintenance events for European high-voltage lines. Your Pydantic AI agent monitors these events to predict grid congestion before it triggers price spikes. To assess the supply side, the agent queries `get_generation_outages` to find offline power plants. This MCP Server integration lets you build resilient monitoring systems that fail loudly if the underlying data structure changes.

Setup guide

Set up ENTSO-E MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 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": {
        "entso-e-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to ENTSO-E tools.",
)

result = await agent.run("List recent ENTSO-E transactions")
print(result.output)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ENTSO-E. 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 ENTSO-E MCP in Pydantic AI

Use the unified toolset class pointing to your Vinkius HTTP endpoint and pass it to your agent's configuration. This approach handles the underlying connection while exposing all 12 energy tools.
Pydantic AI will instantly raise a validation error instead of passing bad data to your agent. This prevents your model from making decisions based on corrupted load or generation strings.
Yes, you can define a Pydantic model that restricts inputs to valid ENTSO-E bidding zone strings. Your agent will validate the area codes before calling tools like `get_actual_load`, saving API quota.
The framework reads the XML response from the tool and validates it against your defined schema. You can parse the generation values by fuel type directly into typed Python objects for safe downstream processing.
Vinkius processes all API requests in ephemeral V8 isolates, securing your ENTSO-E keys from exposure. The validated load and pricing payloads are delivered directly to your application without being cached or logged on Vinkius servers.

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