How to Use the ENTSO-E MCP in AutoGen

Q: How do I register the ENTSO-E MCP Server with AutoGen agents?

You use the mcpservertools function to fetch the tools from the Vinkius endpoint, then pass them directly to your AssistantAgent. This exposes tools like getwindsolarforecast to the agent's conversational loop.

Q: How do AutoGen agents handle XML responses from ENTSO-E?

The raw XML returned by tools like getdayaheadgeneration is fed directly into the agent's conversation history. The agents then parse and discuss the XML values to reach a consensus on regional generation trends.

Let specialized AutoGen agents debate grid stability and market pricing using live ENTSO-E metrics.

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Connect ENTSO-E MCP to AutoGen

Create your Vinkius account to connect ENTSO-E 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.

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Setup ENTSO-E with AutoGen

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Orchestrate agent debates on European grid stability

The `get_actual_generation` tool allows your AutoGen agents to pull physical energy outputs directly into their conversational loops. A dedicated supply agent can analyze wind and solar metrics while a demand agent challenges those findings. They negotiate directly in the conversation thread to flag potential shortfalls before they occur. This collaborative structure prevents individual analytical errors by forcing agents to cross-examine physical grid data.

Resolve energy pricing discrepancies via AutoGen consensus

The `get_day_ahead_prices` tool enables your AutoGen agents to debate market valuations before committing to a trading strategy. One agent identifies low-cost bidding zones while another checks actual grid constraints to calculate risk. By debating these metrics, the agents converge on an optimized bidding strategy. This multi-agent verification process ensures that no trade is recommended without a thorough analysis of both day-ahead and real-time pricing signals.

Evaluate cross-border limits using this MCP Server

The `get_crossborder_flows` tool provides your AutoGen agents with the scheduled energy transfer metrics needed to evaluate cross-border transmission limits. Agents representing different bidding zones debate these values in real time to adjust simulated transfers. By resolving these bottlenecks inside the conversational loop, this MCP Server helps prevent unfeasible transaction proposals. The final consensus reflects both physical capacity limits and scheduled flows.

Setup guide

Set up ENTSO-E 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 ENTSO-E 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="ENTSO-E_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent ENTSO-E 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="ENTSO-E_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent ENTSO-E 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 ENTSO-E. 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 ENTSO-E MCP in AutoGen

You use the mcp_server_tools function to fetch the tools from the Vinkius endpoint, then pass them directly to your AssistantAgent. This exposes tools like `get_wind_solar_forecast` to the agent's conversational loop.

Yes, the McpToolAdapter allows AutoGen agents to execute multiple tools like `get_generation_outages` and `get_installed_generation` in parallel if they need to gather physical capacity data quickly.

The raw XML returned by tools like `get_day_ahead_generation` is fed directly into the agent's conversation history. The agents then parse and discuss the XML values to reach a consensus on regional generation trends.

Yes, you can set up a supervisor agent that monitors a group conversation and decides when to call `get_day_ahead_load` to resolve a disagreement about regional demand forecasts.

Because Vinkius runs the MCP Server in an ephemeral sandbox, your AutoGen agents never have direct access to your API keys. They only interact with the tools to fetch XML power market data, keeping your underlying authentication details completely secure.

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

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