How to Use the U.S. EIA Energy Data MCP in AutoGen

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Connect U.S. EIA Energy Data MCP to AutoGen

Create your Vinkius account to connect U.S. EIA Energy Data 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 U.S. EIA Energy Data with AutoGen

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Perplexity

Multi-Agent Energy Audits

You can set up agents to debate the current energy outlook. For example, a 'Risk Agent' might call `list_petroleum_prices` and flag volatility. A 'Performance Agent' then challenges that risk by calling `quick_us_energy_audit` to provide counter-data.

Deliberating Production Mixes

Need a decision on the best energy mix? Have one agent check natural gas supply using `list_natural_gas_production`. Then, have another agent compare that finding against renewable data from `list_renewable_energy_stats`, forcing them to negotiate a consensus conclusion.

Cross-Regional Price Negotiation

This is where AutoGen shines. Give one agent the role of analyzing regional fuel variations via `list_regional_fuel_prices`. Then, have another agent challenge that finding by cross-referencing it with overall petro data from `list_petroleum_prices`, forcing a reasoned decision.

Setup guide

Set up U.S. EIA Energy Data 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 U.S. EIA Energy Data 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="U.S. EIA Energy Data_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="U.S. EIA Energy Data_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent U.S. EIA Energy Data 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 U.S. EIA Energy Data. 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 U.S. EIA Energy Data MCP in AutoGen

AutoGen allows multiple agents to discuss conflicting findings. If one agent uses `list_coal_production` and concludes a decline, another can challenge that by showing recent growth data from the same server, forcing a more nuanced decision.

Yes. You can build systems where different agents take on specialized roles—one handling gas metrics (`list_natural_gas_production`), and another handling electricity metrics (`list_electricity_generation`)—and they work together to solve the problem.

The server provides tools covering a wide range: from regional fuel pricing and petroleum costs, to comprehensive renewable stats and general energy audits via `quick_us_energy_audit`.

No. While the data source is specific, you control the debate parameters. You can force agents to argue about anything from coal vs. gas production using `list_coal_production` and `list_natural_gas_production`.

It exposes structured tools that let agents retrieve specific metrics, including time-series generation data, fuel supply numbers, and detailed market pricing information.

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