How to Use the Corrently Energy MCP in AutoGen

Q: How do AutoGen agents resolve conflicting recommendations using Corrently Energy?

One agent can use getmarketdata to push for lowest cost, while another uses getco2meter to prioritize low emissions. They debate the outputs inside the AutoGen group chat to find a balanced zip code schedule.

Q: Can I register Corrently Energy tools to specific AutoGen agents?

Yes, you can register tools like getgsiprediction to a specialized Green Energy Agent while assigning getstromkontobalance to a Billing Agent using the MCP tool adapter.

Run multi-agent debates in AutoGen using this MCP Server to optimize German energy schedules.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Corrently Energy MCP to AutoGen

Create your Vinkius account to connect Corrently Energy to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Corrently Energy with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-agent energy scheduling in AutoGen

This MCP Server exposes tools like `create_energy_schedule` to let your AutoGen agents debate and converge on the best charging window. A cost-sensitive agent checks prices while a green-focused agent checks carbon intensity, using the server to resolve conflicts. By calling `get_best_hour` with a German zip code, the agents negotiate the optimal runtimes for heavy machinery. The conversation converges on a concrete schedule that balances financial savings with environmental targets.

Automated hybrid vehicle charging negotiations

The `get_phev_charge_or_fuel` tool provides the core data for agent-to-agent negotiation regarding hybrid vehicle charging. One agent represents the driver's budget while another represents battery longevity, debating the best course of action. They pull real-time grid pricing using `get_market_data` to back up their arguments. This multi-agent setup ensures that the final charging decision is thoroughly vetted from both an economic and ecological perspective.

Verify grid dispatch and merit order data

The `get_dispatch` tool lets your AutoGen analyst agents check the exact breakdown of renewable energy entering the German grid. The agents analyze wind and solar inputs to verify if clean power is actually available in a specific zip code. They cross-reference this with `get_merit_order_list` to understand which conventional power plants are driving up prices. This collaborative analysis produces a detailed report on grid efficiency without human intervention.

Setup guide

Set up Corrently Energy MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Corrently Energy tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Corrently Energy_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Corrently Energy data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Corrently Energy_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Corrently Energy data")
    print(result.messages[-1].content)

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Corrently Energy now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Corrently Energy MCP in AutoGen

One agent can use `get_market_data` to push for lowest cost, while another uses `get_co2_meter` to prioritize low emissions. They debate the outputs inside the AutoGen group chat to find a balanced zip code schedule.

Yes, you can register tools like `get_gsi_prediction` to a specialized Green Energy Agent while assigning `get_stromkonto_balance` to a Billing Agent using the MCP tool adapter.

The server runs inside a V8 Isolate on Vinkius, which handles concurrent requests from multiple AutoGen agents querying German grid data simultaneously without performance degradation.

Your agents must supply a 5-digit German zip code and the solar panel capacity in kWp to the `get_solar_prediction` tool. The agent extracts these parameters from user prompts before initiating the tool call.

The Vinkius zero-trust execution environment ensures that zip codes passed to `get_co2_prediction` and account IDs passed to `get_stromkonto_balance` remain ephemeral. No persistent data is stored outside your local AutoGen session.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript