REE MCP Server

Get time-series data for a specific electricity indicator.

Retrieves historical data for any REE indicator (demand, generation, prices, etc.) for a specified date range. Returns the data with statistical summary.

Args: indicator_id: The indicator ID (e.g., 1293 for real demand, 549 for nuclear) start_date: Start datetime in ISO format (YYYY-MM-DDTHH:MM) end_date: End datetime in ISO format (YYYY-MM-DDTHH:MM) time_granularity: Time aggregation level (raw, hour, day, fifteen_minutes)

Returns: JSON string with indicator metadata, time-series values, and statistics.

Examples: Get hourly real demand for Oct 8, 2025: >>> await get_indicator_data(1293, "2025-10-08T00:00", "2025-10-08T23:59", "hour")

List all available electricity indicators from REE.

Returns metadata for all 1,967+ available indicators including their IDs, names, units, frequencies, and geographic scopes.

Args: limit: Maximum number of indicators to return (default: all) offset: Number of indicators to skip for pagination (default: 0)

Returns: JSON string with list of indicator metadata.

Examples: Get first 50 indicators: >>> await list_indicators(limit=50, offset=0)

Search for indicators by keyword in their names.

Searches through all available indicators and returns those matching the keyword in their name or short name.

Args: keyword: Keyword to search for (e.g., "demanda", "precio", "solar") limit: Maximum number of results (default: 20)

Returns: JSON string with matching indicator metadata.

Examples: Find all demand-related indicators: >>> await search_indicators("demanda", limit=10)

Get a summary of electricity demand for a specific date.

Convenience tool that fetches key demand indicators (real demand, forecast, max/min) for a given date.

Args: date: Date in YYYY-MM-DD format (default: 2025-10-08)

Returns: JSON string with demand summary.

Examples: Get today's demand summary: >>> await get_demand_summary("2025-10-11")

Get the electricity generation mix at a specific time.

Returns the power generation breakdown by source (nuclear, wind, solar, etc.) for a specific hour.

Args: date: Date in YYYY-MM-DD format hour: Hour in HH format (00-23, default: 12)

Returns: JSON string with generation mix by source.

Examples: Get generation mix at noon on Oct 8: >>> await get_generation_mix("2025-10-08", "12")

Get international electricity exchanges at a specific time.

Returns import/export data by country (Andorra, Morocco, Portugal, France) with net balance calculations.

Args: date: Date in YYYY-MM-DD format hour: Hour in HH format (00-23, default: 12)

Returns: JSON string with imports, exports, and net balance by country.

Examples: Get exchanges at noon on Oct 8: >>> await get_international_exchanges("2025-10-08", "12")

Get renewable energy generation summary at a specific time.

Aggregates wind, solar PV, solar thermal, and hydro generation with renewable percentage calculations.

Args: date: Date in YYYY-MM-DD format hour: Hour in HH format (00-23, default: 12)

Returns: JSON string with renewable generation breakdown and percentages.

Examples: Get renewable summary at noon: >>> await get_renewable_summary("2025-10-08", "12")

Get carbon intensity over time (gCO2/kWh).

Calculates CO2 emissions per unit of electricity generated. Lower values indicate cleaner energy mix.

Args: start_date: Start datetime in ISO format (YYYY-MM-DDTHH:MM) end_date: End datetime in ISO format (YYYY-MM-DDTHH:MM) time_granularity: Time aggregation (raw, hour, day, fifteen_minutes)

Returns: JSON string with carbon intensity time series and statistics.

Examples: Get hourly carbon intensity for a day: >>> await get_carbon_intensity("2025-10-08T00:00", "2025-10-08T23:59", "hour")

Compare forecasted vs actual electricity demand.

Calculates forecast accuracy metrics (error, MAE, RMSE) for demand predictions.

Args: date: Date in YYYY-MM-DD format

Returns: JSON string with forecast comparison and accuracy metrics.

Examples: Compare forecast accuracy for Oct 8: >>> await compare_forecast_actual("2025-10-08")

Get grid stability metrics at a specific time.

Analyzes synchronous generation (provides inertia) vs variable renewables (no inertia) to assess grid stability risk.

Args: date: Date in YYYY-MM-DD format hour: Hour in HH format (00-23, default: 12)

Returns: JSON string with grid stability analysis.

Examples: Get grid stability at noon: >>> await get_grid_stability("2025-10-08", "12")

Get generation mix over time for a full day or period.

Returns generation breakdown by source across multiple time points, useful for visualizing energy transition patterns.

Args: date: Date in YYYY-MM-DD format time_granularity: Time aggregation (hour or day, default: hour)

Returns: JSON string with generation mix timeline.

Examples: Get hourly generation mix for a day: >>> await get_generation_mix_timeline("2025-10-08", "hour")

Get Spanish hourly electricity prices (SPOT market) for a specific day.

Returns the 24 hourly prices for the Spanish Peninsular market (OMIE/MIBEL). This is the simplified version focused only on Spain, perfect for checking daily electricity costs.

Args: date: Date in YYYY-MM-DD format

Returns: JSON string with hourly prices, min/max/average, and the cheapest/most expensive hours.

Examples: Get today's hourly prices: >>> await get_spain_hourly_prices("2025-10-19")

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 pumped storage operations for a day.

Shows pumping consumption (storing energy) and turbining (releasing energy) to identify arbitrage opportunities and storage efficiency.

Args: date: Date in YYYY-MM-DD format

Returns: JSON string with storage operations and efficiency metrics.

Examples: Get storage operations for Oct 8: >>> await get_storage_operations("2025-10-08")

Get peak demand analysis over a period.

Analyzes daily maximum and minimum demand to identify patterns and calculate load factors.

Args: start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format

Returns: JSON string with peak demand analysis.

Examples: Get peak analysis for a week: >>> await get_peak_analysis("2025-10-01", "2025-10-07")

Get the PVPC regulated electricity rate at a specific time.

Returns the PVPC (Precio Voluntario para el Pequeño Consumidor) rate, which is the regulated retail electricity price for consumers in Spain.

Args: date: Date in YYYY-MM-DD format hour: Hour in HH format (00-23, default: 12)

Returns: JSON string with PVPC rate data.

Examples: Get PVPC rate at noon on Oct 8: >>> await get_pvpc_rate("2025-10-08", "12")

Get daily demand statistics for a period.

Provides comprehensive daily demand analysis including maximum, minimum, and sum of generation values for each day in the specified period.

Args: start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format

Returns: JSON string with daily statistics and overall summary.

Examples: Get statistics for a week: >>> await get_daily_demand_statistics("2025-10-01", "2025-10-07")

Analyze demand volatility patterns over a period.

Calculates daily demand swings, load factors, and volatility levels to identify high-variability days and overall stability patterns.

Args: start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format

Returns: JSON string with volatility analysis and stability assessment.

Examples: Analyze volatility for a week: >>> await analyze_demand_volatility("2025-10-01", "2025-10-07")