How to Use the EIA Petroleum — Oil Market Intelligence MCP in AutoGen

Fuel debates between your AutoGen agents with live oil market data.

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Connect EIA Petroleum — Oil Market Intelligence MCP to AutoGen

Create your Vinkius account to connect EIA Petroleum — Oil Market Intelligence 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 EIA Petroleum — Oil Market Intelligence with AutoGen

Ask AI about this MCP

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Perplexity

Agents That Argue with Data

With AutoGen, you set up a debate, not just a query. Create an 'Analyst' agent that uses `get_petroleum_prices` to argue for an SPR release. Then pit it against a 'RiskManager' agent that uses `get_petroleum_stocks` to show why that's a bad idea. The agents go back and forth, using the data to challenge each other's points. This surfaces risks and assumptions a single-agent system would miss. The final output isn't just an answer; it's a negotiated consensus.

Model Competing Priorities

Assign different agents competing goals. A 'Producer' agent uses `get_crude_production` data to argue for policies that boost domestic output. A 'Consumer' agent watches `get_petroleum_prices` and argues for lower gas prices. The EIA tools provide the shared reality they all operate from. You're not just getting a forecast; you're simulating a market with different actors. The conversation reveals the real-world trade-offs.

An AutoGen Conversation Starter

This MCP Server gives your team of agents something real to talk about. The tool schemas are automatically adapted for AutoGen, so they can start working right away. No complex setup required. You can stand up a `summarizer_agent` that pulls the `get_petroleum_summary` report and an `importer_agent` that focuses on `get_crude_imports`. Then your `user_proxy_agent` can ask them to debate the impact on trade balance. It's a team of specialists in a box.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence 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 EIA Petroleum — Oil Market Intelligence 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="EIA Petroleum — Oil Market Intelligence_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent EIA Petroleum — Oil Market Intelligence 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="EIA Petroleum — Oil Market Intelligence_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent EIA Petroleum — Oil Market Intelligence data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about EIA Petroleum — Oil Market Intelligence MCP in AutoGen

You provide the EIA tools to one or more agents in your group chat. An agent can then decide to use a tool like `get_petroleum_prices`, and its output becomes a message in the conversation that other agents can see and react to.

Absolutely. You can create an 'ImportsAnalyst' agent that only has access to `get_crude_imports` and a 'ProductionAnalyst' that only has `get_crude_production`. This is a core feature of building specialist agent teams in AutoGen.

A consensus might be a final message from a manager agent that summarizes the debate, weighs the data provided by different specialist agents, and presents a final conclusion that balances the competing viewpoints.

Yes. You can load the tools from this server and pass them directly to an `AssistantAgent` during its creation. The `McpToolAdapter` handles the conversion so the agent can use the tools in its conversations.

Agents share public oil market data fetched from the EIA tools, like crude import volumes or refinery stats. Vinkius isolates your entire multi-agent session in a secure, single-tenant environment. What happens in your conversation stays in your conversation.

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