Do I need an API token to use the Corrently Energy MCP server?

No! Most Corrently API endpoints work without authentication. An optional token is only needed if you want higher rate limits for heavy usage. Simply subscribe to the server and start querying energy data immediately.

What German zip codes are supported for energy forecasts?

All German Postleitzahl (PLZ) 5-digit zip codes are supported — from 01067 (Dresden) to 80331 (Munich). Simply provide any valid German zip code and the API will return localized energy forecasts for that region's grid area.

Can I use this MCP server to optimize when I charge my electric vehicle?

Absolutely! Use the `get_best_hour` tool to find optimal charging windows based on renewable energy availability or lowest CO₂ emissions. Then use `create_energy_schedule` to generate a full optimized charging plan. You can also use `get_phev_charge_or_fuel` if you drive a plug-in hybrid and need advice on whether to charge electrically or use fuel.

How accurate are the solar generation predictions for my photovoltaic system?

The `get_solar_prediction` tool provides forecasts based on weather models and your system's kWp capacity. Accuracy depends on location, panel orientation, and weather conditions. It's best used for relative comparisons (e.g., "Will tomorrow be sunnier than today?") rather than absolute precision. For typical home systems (5-10 kWp), day-ahead forecasts are generally within 15-25% of actual generation.

Corrently Energy MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Corrently Energy
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Corrently Energy through Vinkius, pass the Edge URL in the `mcps` parameter and every Corrently Energy tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Corrently Energy Specialist",
    goal="Help users interact with Corrently Energy effectively",
    backstory=(
        "You are an expert at leveraging Corrently Energy tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Corrently Energy "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Corrently Energy MCP Server

Connect to Corrently Energy APIs and bring real-time German energy market intelligence to any AI agent. Monitor renewable energy availability, optimize consumption schedules, and make data-driven decisions for sustainable power usage.

When paired with CrewAI, Corrently Energy becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Corrently Energy tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

GrünstromIndex (GSI) — Get hourly forecasts for renewable energy availability, showing when green power from wind and solar is most abundant
CO₂ Predictions — Track carbon intensity of electricity consumption by German zip code with real-time and forecasted emissions data
Best Hour Finder — Automatically identify optimal time windows for energy-intensive activities based on renewable peaks and lowest CO₂
Market Data — Access current electricity market prices, wholesale costs, and regional pricing forecasts
Solar Forecasts — Predict photovoltaic generation output for specific solar installations based on location and capacity (kWp)
Energy Scheduling — Create intelligent operating schedules for EVs, heat pumps, and industrial equipment optimized for price, solar, or emissions
Merit Order — View the current energy generation mix showing which power plants are active and their cost efficiency
Real-Time CO₂ Meter — Check instant carbon intensity readings (g CO₂/kWh) for any German location
PHEV Decision Support — Get smart advice for plug-in hybrid drivers on whether to charge electrically or use fuel
CO₂ Offset Calculator — Calculate compensation requirements and available options for neutralizing carbon footprints
Renewable Dispatch — Monitor renewable energy feed-in data showing wind and solar contributions to the grid
Stromkonto Balance — Check electricity account balances and green energy certificates

The Corrently Energy MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Corrently Energy to CrewAI via MCP

Follow these steps to integrate the Corrently Energy MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Corrently Energy

Why Use CrewAI with the Corrently Energy MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Corrently Energy through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Corrently Energy + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Corrently Energy MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Corrently Energy for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Corrently Energy, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Corrently Energy tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Corrently Energy against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Corrently Energy MCP Tools for CrewAI (12)

These 12 tools become available when you connect Corrently Energy to CrewAI via MCP:

calculate_co2_offset

Helps users understand how to neutralize their carbon footprint. USE WHEN: - User asks how to offset their CO₂ emissions - User wants to calculate carbon compensation needed - User needs information about CO₂ compensation options - User asks about neutralizing their carbon footprint from activities PARAMETERS: - co2_kg (REQUIRED): Amount of CO₂ in kilograms to offset (minimum: 0.1) - activity_type (OPTIONAL): Type of activity that generated emissions (e.g. "flight", "car", "heating") EXAMPLES: - "How much does it cost to offset 500 kg of CO₂?" → call with co2_kg=500 - "Calculate offset for my flight emissions" → call with co2_kg=250, activity_type="flight" - "I drove 1000km, what is the CO₂ compensation?" → call with co2_kg=180, activity_type="car" Calculate CO₂ offset requirements and available compensation options

create_energy_schedule

Schedules are optimized based on electricity prices, solar generation peaks, CO₂ emissions, or comfort levels. USE WHEN: - User wants to create an automated schedule for energy devices - User needs to optimize when to run appliances for cost or green energy - User asks to schedule energy consumption for the next hours - User wants smart scheduling for their heat pump, EV charger, or machinery PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits - hours (REQUIRED): Number of hours for the schedule operation (1-36 hours) - optMode (OPTIONAL): Optimization mode - "price" (cheapest), "solar" (max solar), "emission" (lowest CO₂), "comfort" (balanced). Default: "price" EXAMPLES: - "Create a 12-hour schedule for Berlin 10115 optimized for lowest price" → call with zip="10115", hours=12, optMode="price" - "Schedule my EV charging for next 8 hours in Munich using solar energy" → call with zip="80331", hours=8, optMode="solar" - "Optimize my heat pump for 24 hours with lowest emissions in Hamburg" → call with zip="20095", hours=24, optMode="emission" Create an optimized energy schedule for appliances and devices

get_best_hour

Perfect for scheduling energy-intensive activities. USE WHEN: - User asks when is the best time to use energy-intensive appliances - User wants to optimize energy consumption for green power or low emissions - User needs to schedule operations during clean energy peaks - User asks about optimal charging times for EVs or running machinery PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits - hours (OPTIONAL): Number of consecutive hours needed (default: 1, min: 1, max: 168) EXAMPLES: - "When is the best 3-hour window to run my dishwasher in Berlin 10115?" → call with zip="10115", hours=3 - "Best time to charge my EV in Munich tonight" → call with zip="80331", hours=6 - "When should I use high-power appliances today?" → call with zip="70173", hours=2 Find the best hours for energy consumption based on renewable availability and low CO₂ emissions

get_co2_meter

Shows grams of CO₂ per kWh right now. USE WHEN: - User asks about current/real-time CO₂ levels in the electricity grid - User wants instant carbon intensity data - User needs to know how clean/dirty the electricity is right now - User asks about live carbon emissions from power PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits EXAMPLES: - "What is the current CO₂ intensity in Berlin 10115?" → call with zip="10115" - "Show me real-time carbon levels for Munich 80331" → call with zip="80331" - "Current CO₂ emissions from electricity in Cologne" → call with zip="50667" Get real-time CO₂ meter readings for a German zip code

get_co2_prediction

Shows how carbon-intensive the power grid will be over time. USE WHEN: - User asks about CO₂ emissions or carbon footprint of electricity - User wants to know when electricity is cleanest/lowest emissions - User needs carbon intensity data for a location PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits EXAMPLES: - "What are the CO₂ emissions for Hamburg 20095?" → call with zip="20095" - "Show carbon intensity for Frankfurt 60311" → call with zip="60311" Get CO₂ emissions forecast for electricity consumption in Germany

get_dispatch

Shows how much renewable energy is being fed into the grid and its composition. USE WHEN: - User asks about renewable energy feed-in for a location - User needs dispatch data for renewable energy sources - User wants to understand the renewable energy flow in their area - User asks about wind and solar contribution to the grid PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits EXAMPLES: - "Show renewable energy dispatch for Berlin 10115" → call with zip="10115" - "How much renewable energy is being fed into the grid in Munich?" → call with zip="80331" - "Wind and solar dispatch for Hamburg 20095" → call with zip="20095" Get renewable energy dispatch information for a German zip code

get_gsi_prediction

USE WHEN: - User asks about green energy availability or renewable power forecast - User wants to know the GrünstromIndex or GSI for a location - User needs to understand when clean energy is most abundant PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits, e.g. "10115" for Berlin - token (OPTIONAL): API token for higher rate limits - auto-provided from credentials EXAMPLES: - "What is the renewable energy forecast for Berlin 10115?" → call with zip="10115" - "Show me the green power index for Munich 80331" → call with zip="80331" Get GrünstromIndex (Green Power Index) prediction for a German zip code

get_market_data

Includes wholesale prices and regional cost data. USE WHEN: - User asks about electricity prices or costs in a specific location - User needs market data, wholesale prices, or energy cost forecasts - User wants to compare energy costs across time periods - User asks about cheap/expensive electricity hours PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits EXAMPLES: - "What are current electricity prices in Berlin 10115?" → call with zip="10115" - "Show me energy market data for Cologne 50667" → call with zip="50667" - "When is electricity cheapest today in Stuttgart 70173?" → call with zip="70173" Get current electricity market data and pricing information for a German location

get_merit_order_list

This shows which energy sources are being used to generate electricity and their cost efficiency. USE WHEN: - User asks about the current energy generation mix - User wants to understand which power plants are active - User needs merit order data for market analysis - User asks about energy source prioritization in the grid EXAMPLES: - "Show me the current merit order list" → call with no extra params - "What energy sources are currently generating power?" → call with no extra params - "Merit order ranking for Germany" → call with no extra params Get the current merit order list for the German energy market

get_phev_charge_or_fuel

USE WHEN: - User asks whether to charge their PHEV or use fuel - PHEV driver needs advice on optimal energy source - User wants to know if now is a good time to charge their hybrid - User asks about cost-efficiency of electric vs fuel for their PHEV PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits EXAMPLES: - "Should I charge my PHEV or use fuel in Berlin 10115?" → call with zip="10115" - "Charge or fuel decision for Munich 80331" → call with zip="80331" - "Is now a good time to charge my hybrid in Hamburg?" → call with zip="20095" Get decision support for plug-in hybrid (PHEV) drivers - charge or fuel

get_solar_prediction

Shows expected energy production over time. USE WHEN: - User asks about solar panel output or PV system generation - User needs forecasts for their solar installation - User wants to know expected renewable energy production - User asks how much energy their solar panels will generate PARAMETERS: - zip (REQUIRED): German zip code (Postleitzahl) - exactly 5 digits - kwp (REQUIRED): Solar panel capacity in kilowatt peak (kWp), range: 0.1 to 1000 EXAMPLES: - "How much energy will my 5 kWp solar system generate in Berlin 10115?" → call with zip="10115", kwp=5 - "Solar forecast for my 10 kWp installation in Munich 80331" → call with zip="80331", kwp=10 - "Expected PV output for 3.5 kWp in Hamburg 20095" → call with zip="20095", kwp=3.5 Get solar energy generation forecast for a photovoltaic installation

get_stromkonto_balance

Shows credits, green energy certificates, and account status. USE WHEN: - User asks about their electricity account balance - User wants to check their Stromkonto status - User needs information about their green energy credits or certificates - User asks about their energy account PARAMETERS: - account (REQUIRED): Account identifier for the Stromkonto EXAMPLES: - "Check my Stromkonto balance for account 0x123abc" → call with account="0x123abc" - "Show my energy account status" → call with account="USER_ACCOUNT_ID" Get Stromkonto (electricity account) balance information

Example Prompts for Corrently Energy in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Corrently Energy immediately.

"What is the renewable energy forecast for Berlin zip code 10115 today?"

"When is the best 4-hour window to run my dishwasher in Munich 80331 to use the greenest energy?"

"Show me current electricity market prices for Hamburg 20095 and tell me when it's cheapest today."

Troubleshooting Corrently Energy MCP Server with CrewAI

Common issues when connecting Corrently Energy to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Corrently Energy + CrewAI FAQ

Common questions about integrating Corrently Energy MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.