How to Use the Enverus Energy Intelligence MCP in AutoGen

Q: How do I configure AutoGen to use the Enverus Energy Intelligence MCP tools?

Install autogen-extmcp. Use mcpservertools with StreamableHttpServerParams to fetch the tools. AutoGen handles the schema conversion automatically via McpToolAdapter.

Q: Can multiple AutoGen agents call Enverus Energy Intelligence tools simultaneously?

Yes. A basin analyst agent can run listbasinspecificactivity while a market analyst agent queries getenergymarketintelligencesummary. They bring their respective findings back to the group chat.

Q: How do AutoGen agents handle Enverus Energy Intelligence API errors?

If an agent calls getenverusapimetadata and receives an auth error, it informs the group. A debugging agent can then suggest configuration changes or ask you for a valid token.

Deploy debating AutoGen agents to analyze Enverus rig telemetry via this MCP Server and negotiate asset valuations.

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Setup Enverus Energy Intelligence with AutoGen

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Debate Well Telemetry Metrics

The `get_well_production_telemetry` tool gives your AutoGen agents raw historical production data from the MCP Server to argue over. A risk-assessment agent pulls the decline curves while a financial agent projects future cash flow based on the same numbers. They don't agree immediately. The risk agent might call `list_oil_and_gas_wells` to compare nearby asset performance, forcing the financial agent to revise its optimistic forecast before presenting you with a final verdict. Bottom line: you get vetted numbers.

Track Rigs via AutoGen MCP Server

The `list_active_drilling_rigs` tool lets your agents map current deployment across the continent. One agent monitors the list for new additions while a secondary agent verifies the hardware using `get_rig_technical_details`. This creates a self-correcting research loop. If the technical details show a rig is unsuitable for deep shale, the monitoring agent flags the discrepancy and drops the asset from the acquisition target list.

Negotiate M&A Strategies

The `list_energy_m_and_a_deals` tool feeds recent sector transactions into your agent chat. A strategy agent uses these comps to set a baseline valuation for targeted acreage. A counter-agent then pulls `list_drilling_permits` to see if competitors are already moving into the same basin. They negotiate the strategic value of the land, using hard permit data to justify every counteroffer.

Setup guide

Set up Enverus Energy 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 Enverus Energy 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="Enverus Energy Intelligence_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Enverus Energy Intelligence 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="Enverus Energy Intelligence_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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

Install `autogen-ext[mcp]`. Use `mcp_server_tools` with `StreamableHttpServerParams` to fetch the tools. AutoGen handles the schema conversion automatically via `McpToolAdapter`.

Yes. A basin analyst agent can run `list_basin_specific_activity` while a market analyst agent queries `get_energy_market_intelligence_summary`. They bring their respective findings back to the group chat.

If an agent calls `get_enverus_api_metadata` and receives an auth error, it informs the group. A debugging agent can then suggest configuration changes or ask you for a valid token.

Single agents accept the first answer they get. AutoGen forces an asset audit from `quick_energy_asset_audit` to survive scrutiny from a skeptical critic agent before you see the result.

Your multi-agent chat history never touches our servers. The agents pull raw transaction data via `list_energy_m_and_a_deals` through a stateless execution layer. Vinkius has zero visibility into your internal negotiations or the deal terms.

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