OpenEI MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to OpenEI through Vinkius, pass the Edge URL in the `mcps` parameter and every OpenEI tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="OpenEI Specialist",
goal="Help users interact with OpenEI effectively",
backstory=(
"You are an expert at leveraging OpenEI 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 OpenEI "
"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)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About OpenEI MCP Server
Access the National Utility Rate Database through OpenEI — the most comprehensive source for US electricity rate data maintained by the Department of Energy. Connect OpenEI to your AI agent to instantly query utility rates by address or coordinates, analyze rate structures across residential, commercial, and industrial sectors, retrieve complete tariff details including time-of-use periods and demand charges — all through natural conversation.
When paired with CrewAI, OpenEI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call OpenEI 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
- Location-Based Rate Lookup — Find all applicable utility rates by providing a street address or GPS coordinates.
- Sector-Specific Rates — Query residential, commercial, or industrial electricity rates separately.
- Complete Tariff Analysis — Retrieve full rate structures including time-of-use periods, seasonal variations, demand charges, and energy charges.
- Utility Company Research — Search and browse US electric utilities, get company details and service territories.
- Solar Feasibility Studies — Instant rate quotes for solar ROI calculations and net metering analysis.
- Energy Cost Modeling — Access detailed rate structures for accurate energy cost projections.
- Demand Charge Analysis — Understand demand charges for commercial and industrial facilities.
- Rate Comparison — Compare rate options across different utilities and locations.
The OpenEI 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 OpenEI to CrewAI via MCP
Follow these steps to integrate the OpenEI 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 OpenEI
Why Use CrewAI with the OpenEI MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with OpenEI 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
OpenEI + CrewAI Use Cases
Practical scenarios where CrewAI combined with the OpenEI MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries OpenEI 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 OpenEI, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain OpenEI 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 OpenEI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
OpenEI MCP Tools for CrewAI (10)
These 10 tools become available when you connect OpenEI to CrewAI via MCP:
get_commercial_rates
Use lat/lon or address to identify the location. Returns all available commercial tariffs including general service, large power, and time-of-use rates. Essential for commercial solar installations, demand response analysis, and business energy cost modeling. Get commercial electricity rates for a location
get_industrial_rates
Industrial rates typically include the lowest per-kWh costs but may have complex demand charges and power factor adjustments. Use for heavy manufacturing energy cost analysis, load forecasting, and industrial facility site selection. Get industrial electricity rates for a location
get_rate_detail
Returns the full rate structure including energy charges, demand charges, fixed charges, minimum charges, time-of-use periods, seasonal variations, and applicable taxes. Use this after identifying a rate ID from get_utility_rates to get exhaustive details for cost modeling or bill analysis. Get detailed information about a specific utility rate/tariff
get_rates_by_address
Simply provide a street address and the API will geocode it and identify the serving utility and applicable rates. Perfect for solar installers providing instant rate quotes to customers, or homeowners checking their electricity rates. Returns all available rate options at that address. Get utility rates for a specific street address
get_rates_by_coordinates
Automatically identifies the serving utility for that location and returns applicable rates. Essential for solar installers, energy consultants, and site selection analysis. Returns residential, commercial, and industrial rates if available. Set detail=full for complete rate structures. Get utility rates for a location using GPS coordinates
get_residential_rates
Perfect for homeowners comparing electricity costs, evaluating solar ROI, or understanding time-of-use rate options. Returns all residential tariffs including tiered rates, time-of-use plans, and electric vehicle charging rates. Get residential electricity rates for a location
get_utility_detail
Returns the utility name, address, contact information, service territory, owned generation resources, and associated rates. Use this to research utility companies, understand their generation mix, or identify all rates offered by a specific utility. Get detailed information about a specific utility company
get_utility_rates
Provide either latitude/longitude coordinates or a physical address to find applicable utility rates. Filter by sector (residential, commercial, industrial) to get specific rate types. Use detail=full to retrieve complete rate structures including time-of-use periods, seasonal variations, demand charges, and energy charges. This is essential for solar analysis, energy cost modeling, and economic feasibility studies. Sector values: 1=Residential, 2=Commercial, 3=Industrial. Get utility rate information for a specific location
list_utilities
Filter by state, country, or utility name to find specific companies. Returns utility names, addresses, company IDs, and service territories. Use this to identify utility companies for research or to get company IDs for further queries. Use limit and offset for pagination through large result sets. List electric utility companies in the OpenEI database
search_utilities_by_name
Useful for finding the correct utility when you know part of the company name but not the ID. Returns matching utilities with their IDs, addresses, and service areas. Use the returned IDs for detailed queries. Search for utility companies by name
Example Prompts for OpenEI in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with OpenEI immediately.
"What are the residential electricity rates at 1617 Cole Blvd, Golden, CO?"
"Show me all utilities in California and their average commercial rates."
"Get the complete rate structure for commercial time-of-use rates from PG&E."
Troubleshooting OpenEI MCP Server with CrewAI
Common issues when connecting OpenEI to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
OpenEI + CrewAI FAQ
Common questions about integrating OpenEI MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
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?
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?
Can CrewAI agents call multiple MCP tools in parallel?
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)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect OpenEI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect OpenEI to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.