How do I get an Enverus API Key?

You need an active Enverus subscription. Log in to your [**Enverus Developer Portal**](https://developer.enverus.com), navigate to your account settings, and you can generate or retrieve your unique **API Key** from there.

Does the integration cover global basins?

Yes, Enverus tracks asset activity globally. Availability of specific data for basins like Permian, Bakken, or international fields depends on your subscription level and API permissions.

Is production data real-time?

Production data is updated as frequently as reported by operators and regulatory agencies. You can retrieve the latest available telemetry using the get_well_production_telemetry tool.

Enverus Energy Intelligence MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Enverus Energy Intelligence
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Enverus Energy Intelligence through Vinkius, pass the Edge URL in the `mcps` parameter and every Enverus Energy Intelligence tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Enverus Energy Intelligence Specialist",
    goal="Help users interact with Enverus Energy Intelligence effectively",
    backstory=(
        "You are an expert at leveraging Enverus Energy Intelligence tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Enverus Energy Intelligence "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Enverus Energy Intelligence MCP Server

Integrate Enverus, the leading energy SaaS company, directly into your AI workflow. Access real-time data on active drilling rigs and oil/gas wells, track new drilling permits and basin-specific activity, monitor M&A transactions in the energy sector, and oversee market intelligence using natural language.

When paired with CrewAI, Enverus Energy Intelligence becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Enverus Energy Intelligence tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Asset Oversight — List and retrieve detailed information for active drilling rigs and oil/gas wells across various geological basins.
Production Intelligence — Monitor well production telemetry, resolving daily BOE/d volumes and identifying gas-to-oil ratios.
Market Analysis — Access high-level energy market summaries and recent M&A deal data to stay ahead of industry trends.
Energy Auditing — Retrieve high-level summaries of rig counts, well activity, and organizational energy asset health instantly.

The Enverus Energy Intelligence MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Enverus Energy Intelligence to CrewAI via MCP

Follow these steps to integrate the Enverus Energy Intelligence MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Enverus Energy Intelligence

Why Use CrewAI with the Enverus Energy Intelligence MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Enverus Energy Intelligence through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Enverus Energy Intelligence + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Enverus Energy Intelligence MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Enverus Energy Intelligence for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Enverus Energy Intelligence, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Enverus Energy Intelligence tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Enverus Energy Intelligence against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Enverus Energy Intelligence MCP Tools for CrewAI (10)

These 10 tools become available when you connect Enverus Energy Intelligence to CrewAI via MCP:

get_energy_market_intelligence_summary

Retrieve a high-level summary of current energy market trends

get_enverus_api_metadata

Retrieve metadata and authorization status for your Enverus API connection

get_rig_technical_details

Get detailed settings and current activity for a specific rig

get_well_production_telemetry

Get historical and current production data for a specific well

list_active_drilling_rigs

List all active drilling rigs currently tracked in the Enverus database

list_basin_specific_activity

List rigs and wells active within a specific geological basin

list_drilling_permits

List recently issued drilling permits

list_energy_m_and_a_deals

List recent mergers, acquisitions, and asset transactions in the energy sector

list_oil_and_gas_wells

List oil and gas wells within the selected criteria

quick_energy_asset_audit

Retrieve a high-level summary of rig and well counts

Example Prompts for Enverus Energy Intelligence in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Enverus Energy Intelligence immediately.

"List active drilling rigs in the Permian basin."

"Show me production stats for well ID '42-123-45678'."

"What are the latest energy M&A deals?"

Troubleshooting Enverus Energy Intelligence MCP Server with CrewAI

Common issues when connecting Enverus Energy Intelligence to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Enverus Energy Intelligence + CrewAI FAQ

Common questions about integrating Enverus Energy Intelligence MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.