# Corrently Regional Green Index MCP > Corrently Regional Green Index provides hyper-local energy intelligence, allowing you to forecast when a region's power grid is cleanest and check real-time electricity market costs. By querying your AI agent with this MCP, you can schedule high-load tasks (like running washing machines or simulations) for times when the local mix of power is most sustainable. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** green-energy, sustainability, energy-market, forecast-data, carbon-footprint ## Description This connection gives your agent deep intelligence into regional energy flows. You stop guessing about grid sustainability and start planning based on data. It tells you two things: first, how clean the electricity is right now—using a Green Power Index forecast by ZIP code; and second, what that power actually costs at the exchange rate. Whether you're running a smart home or simulating resource-heavy tasks, your agent acts like a dedicated energy consultant. You just ask it to check the optimal timing for consumption based on regional sustainability goals and current market prices. Connecting this MCP through Vinkius lets any compatible AI client route these two data streams together, giving you actionable answers instead of raw spreadsheets. ## Tools ### get_regional_green_index Returns a forecast that tells you when local electricity grids are powered by the most sustainable energy mix for any given ZIP code. ### get_energy_market_data Retrieves the latest available data on wholesale electricity exchange prices and market trends. ## Prompt Examples **Prompt:** ``` What is the green energy index for ZIP code 10117 (Berlin)? ``` **Response:** ``` Checking the Corrently GSI for Berlin... The current index is 62, which is 'Clean'. The cleanest time to consume energy in this region will be tomorrow between 2 PM and 4 PM. Would you like to see the full forecast? ``` **Prompt:** ``` Check the green power forecast for Munich (ZIP 80331). ``` **Response:** ``` Retrieving data for Munich... The grid is currently at a moderate index of 45. However, it is expected to rise to 78 later tonight as wind production increases. It's a great time to schedule heavy loads for 11 PM. ``` **Prompt:** ``` Show me the current energy market prices. ``` **Response:** ``` Fetching market data... The latest exchange price is 85.40 EUR/MWh. Prices have been stable over the last 6 hours. Would you like to see the trend chart data? ``` ## Capabilities ### Assess Grid Cleanliness Forecasts Get a predicted sustainability score for local power grids based on your ZIP code. ### Check Real-Time Market Costs Retrieve the latest price data from electricity exchanges, showing you what energy costs right now. ### Determine Optimal Consumption Windows Identify specific hours when consuming power will minimize your carbon footprint relative to current grid generation. ## Use Cases ### Optimizing Data Center Workloads A DevOps engineer needs to run a massive data processing job. They ask their agent: 'When is the grid cleanest AND cheapest for ZIP 80331?' The agent uses `get_regional_green_index` and `get_energy_market_data` to tell them that running the job tonight between 11 PM and 2 AM maximizes renewable use while market prices are at a local low. ### Planning Residential Solar Integration A homeowner wants to buy an EV charger. They ask their agent: 'What's the best time for charging this week?' The agent checks `get_regional_green_index` and advises them that running the charge between 2 PM and 4 PM on Thursday maximizes solar use, regardless of minor price fluctuations. ### Analyzing Regulatory Compliance An environmental consultant must report on localized sustainability. They instruct their agent to 'Analyze regional grid performance for ZIP 10117 over the last month.' The agent uses `get_regional_green_index` and aggregates market data, providing a clear picture of both compliance metrics and financial risk. ### Forecasting Operational Stress An infrastructure firm needs to know if their current grid capacity is stressed. They ask the agent to 'Compare regional green index trends with recent market price spikes.' The combined data reveals that while the index looks healthy, volatile pricing suggests underlying transmission weaknesses. ## Benefits - You stop running heavy workloads randomly. By using the forecast from `get_regional_green_index`, you schedule high-demand tasks specifically for periods with maximum renewable generation, lowering your footprint. - Cost planning just got smarter. Instead of guessing what energy costs will be, calling `get_energy_market_data` gives you real-time pricing so you can budget infrastructure overhauls accurately. - You gain a holistic view by combining both data sources. Your agent doesn't just tell you the greenest time; it tells you if that clean power is also cost-effective right now. - Avoid unexpected costs and carbon penalties. The MCP helps pinpoint specific optimal windows, letting you plan your usage around sustainability targets and market volatility simultaneously. - Build resilient systems. You can design smart processes that automatically react to changing grid conditions, minimizing both environmental impact and operational expense. ## How It Works The bottom line is you get actionable energy intelligence without needing to manage multiple dashboards or APIs. 1. Subscribe to this MCP on Vinkius. No API key is needed because access is public. 2. Your AI client queries the MCP, asking for specific regional data (like a ZIP code or time frame). 3. The agent pulls both the Green Index forecast and current market prices, giving you a single, combined answer. ## Frequently Asked Questions **What ZIP codes can I use with the get_regional_green_index tool?** The index supports various supported ZIP codes, but you should check the Corrently documentation for the full list of regions available. The agent will confirm if your specific code is supported. **Does this MCP give me historical energy market data?** No, this MCP focuses on current and forecasted conditions. `get_energy_market_data` provides the latest exchange prices, not long-term trend analysis or historical records. **How do I schedule a job using get_regional_green_index?** Simply ask your agent to identify the best time for a specific task. You need to provide both the ZIP code and the required load profile so the MCP can calculate the optimal window. **Are there any fees when I use get_energy_market_data?** The data provided by this MCP is free to access, meaning you don't need to worry about API keys or subscription costs for basic usage. **How do I connect my agent to the get_regional_green_index tool?** You don't need an API key. This MCP provides public access, meaning any compatible client can query the index directly without setting up credentials. **Are there rate limits when using the get_energy_market_data tool?** We monitor usage to ensure reliable service for all users. While we don't publish strict quotas, heavy or excessive querying patterns might encounter temporary limits. **What geographic areas does the get_regional_green_index tool cover?** The index currently focuses on regions within Germany. It is built to provide accurate green power forecasts using German ZIP codes. **How detailed are the predictions from the get_regional_green_index tool?** Forecasts provide time-based predictions, letting you pinpoint specific blocks when the local grid is expected to be cleanest. This helps schedule heavy loads optimally. **Does this work outside of Germany?** The Green Power Index (GSI) is currently most accurate and comprehensive for German ZIP codes. Market data includes broader European exchange info. **What is the GSI scale?** The Green Power Index (GSI) ranges from 0 to 100. A higher value indicates a higher percentage of renewable energy in the regional grid at that specific time. **Can I get market prices for today?** Yes. The `get_energy_market_data` tool retrieves current electricity exchange prices, which are essential for industrial and commercial energy management.