How to Use the Corrently Energy MCP in CrewAI

Q: How do I configure a CrewAI agent to use Corrently Energy tools?

You pass the server URL directly in your agent's mcps array parameter. CrewAI automatically connects to the server and exposes tools like getbesthour to that specific agent.

Q: Can I restrict which Corrently Energy tools a CrewAI agent can see?

Yes, use the MCPServerHTTP class from crewai.mcp and define a toolfilter. This lets you expose getsolarprediction to your solar analyst agent while keeping other tools hidden.

Deploy a crew of autonomous agents to optimize German grid usage with CrewAI and Corrently Energy.

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Connect Corrently Energy MCP to CrewAI

Create your Vinkius account to connect Corrently Energy to CrewAI 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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Setup Corrently Energy with CrewAI

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Multi-Agent Energy Optimization Teams

This MCP Server integrates with specialized agent teams to solve complex German grid problems. One agent monitors live market pricing using `get_market_data`, while another checks local solar forecasts with `get_solar_prediction`. CrewAI agents share memory and pass German energy metrics back and forth. Together, they decide the absolute best time to run heavy operations without relying on a single monolithic prompt.

Autonomous Grid Response with CrewAI and MCP Servers

This MCP Server powers a continuous monitoring crew that watches local grid emissions. A researcher agent checks real-time carbon levels using `get_co2_meter`, while a coordinator agent plans offsets using `calculate_co2_offset`. Everything runs in the background of your CrewAI execution loop. Your crew autonomously calculates carbon compensation requirements for business activities and queue up offset actions based on regional grid dirtiness.

Merit Order Analysis and Market Forecasting

This MCP Server provides financial agents with the tools to analyze energy generation mixes. By calling `get_merit_order_list`, your crew can see which power plants are active and how they affect wholesale pricing. A separate analyst agent cross-references this with `get_dispatch` to understand renewable feed-in trends. Analyzing these metrics gives your CrewAI team a deep look into the German energy market's behavior.

Setup guide

Set up Corrently Energy MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Corrently Energy tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Corrently Energy Analyst",
    goal="Access and analyze Corrently Energy data via MCP.",
    backstory="Expert analyst with direct Corrently Energy access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Corrently Energy transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Corrently Energy Analyst",
        goal="Access and analyze Corrently Energy data via MCP.",
        backstory="Expert analyst with direct Corrently Energy access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Corrently Energy transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Corrently Energy. 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 Corrently Energy MCP in CrewAI

You pass the server URL directly in your agent's `mcps` array parameter. CrewAI automatically connects to the server and exposes tools like `get_best_hour` to that specific agent.

Yes, use the `MCPServerHTTP` class from `crewai.mcp` and define a `tool_filter`. This lets you expose `get_solar_prediction` to your solar analyst agent while keeping other tools hidden.

CrewAI agents use a shared memory pool. When the market analyst agent runs `get_market_data`, the pricing results are immediately available to the scheduling agent to plan optimal run times.

Yes, it covers the entire German electricity grid. You just need to provide a standard five-digit German zip code to get localized forecasts and pricing.

Every request containing location zip codes and solar system capacity (kWp) is processed inside ephemeral V8 isolates. The data is never written to persistent disks or shared with third parties.

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