get_price_analysis
Analyze electricity SPOT market prices over time with statistics and multi-country comparisons. Use geographic filters to focus on specific European markets or compare all countries.
Instructions
Get electricity price analysis over time.
Analyzes SPOT market prices with statistics and multi-country comparison. Note: SPOT price indicator returns data for multiple European countries. Use geo_filter to focus on a specific market.
Args: start_date: Start datetime in ISO format (YYYY-MM-DDTHH:MM) end_date: End datetime in ISO format (YYYY-MM-DDTHH:MM) geo_filter: Optional geographic filter (e.g., "Península", "Portugal", "France") If not specified, returns all countries
Returns: JSON string with price data and analysis.
Examples: Get Spanish hourly prices for a day: >>> await get_price_analysis("2025-10-08T00:00", "2025-10-08T23:59", "Península")
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| end_date | Yes | ||
| geo_filter | No |
Implementation Reference
- The handler function for the 'get_price_analysis' MCP tool. It fetches SPOT market electricity price data for a given date range, optionally filters by geographic scope, groups prices by country, computes statistics (min, max, avg per country), and returns a formatted JSON response with analysis.async def get_price_analysis( start_date: str, end_date: str, geo_filter: str | None = None ) -> str: """Get electricity price analysis over time. Analyzes SPOT market prices with statistics and multi-country comparison. Note: SPOT price indicator returns data for multiple European countries. Use geo_filter to focus on a specific market. Args: start_date: Start datetime in ISO format (YYYY-MM-DDTHH:MM) end_date: End datetime in ISO format (YYYY-MM-DDTHH:MM) geo_filter: Optional geographic filter (e.g., "Península", "Portugal", "France") If not specified, returns all countries Returns: JSON string with price data and analysis. Examples: Get Spanish hourly prices for a day: >>> await get_price_analysis("2025-10-08T00:00", "2025-10-08T23:59", "Península") Get all countries' prices for comparison: >>> await get_price_analysis("2025-10-08T00:00", "2025-10-08T23:59") """ try: async with ToolExecutor() as executor: use_case = executor.create_get_indicator_data_use_case() # Get SPOT price data request = GetIndicatorDataRequest( indicator_id=IndicatorIDs.SPOT_MARKET_PRICE.id, start_date=start_date, end_date=end_date, time_granularity="hour", ) response = await use_case.execute(request) price_data = response.model_dump() values = price_data.get("values", []) # Filter by geography if requested if geo_filter: values = [v for v in values if v["geo_scope"] == geo_filter] # Group by country countries: dict[str, list[dict[str, Any]]] = {} for value_point in values: geo = value_point["geo_scope"] if geo not in countries: countries[geo] = [] countries[geo].append( { "datetime": value_point["datetime"], "price_eur_per_mwh": value_point["value"], } ) # Calculate statistics per country country_stats = {} for country, prices in countries.items(): price_values = [p["price_eur_per_mwh"] for p in prices] if price_values: country_stats[country] = { "min_eur_per_mwh": round(min(price_values), 2), "max_eur_per_mwh": round(max(price_values), 2), "avg_eur_per_mwh": round(sum(price_values) / len(price_values), 2), "count": len(price_values), } result = { "period": {"start": start_date, "end": end_date}, "countries": countries, "statistics_by_country": country_stats, "unit": price_data["indicator"]["unit"], } return ResponseFormatter.success(result) except Exception as e: return ResponseFormatter.unexpected_error(e, context="Error analyzing prices")