How to Use the Ember Climate MCP in CrewAI

Deploy autonomous energy research crews using Ember Climate tools within the CrewAI framework.

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…and any MCP-compatible client

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Connect Ember Climate MCP to CrewAI

Create your Vinkius account to connect Ember Climate to CrewAI 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 Ember Climate with CrewAI

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Claude

Perplexity

Specialized agents for energy research

Assign one agent to analyze `get_electricity_demand_yearly` while another monitors `get_installed_capacity_monthly`. They work as a crew to build a full picture. CrewAI manages the communication between them. You get a cohesive report without directing every single step.

Scale data collection with an MCP Server

Use `get_api_options` to let your agents discover available datasets before they start their work. It ensures your crew always uses valid parameters. This makes your agents more autonomous. They figure out the right way to query the grid data on their own.

Collaborative energy analysis

Share memory between agents to track `get_carbon_intensity_yearly` across multiple sessions. One agent finds the data, the other writes the summary. This MCP Server provides the facts. Your crew does the rest of the heavy lifting.

Setup guide

Set up Ember Climate MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Ember Climate tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Ember Climate Analyst",
    goal="Access and analyze Ember Climate data via MCP.",
    backstory="Expert analyst with direct Ember Climate access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Ember Climate transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Ember Climate Analyst",
        goal="Access and analyze Ember Climate data via MCP.",
        backstory="Expert analyst with direct Ember Climate access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Ember Climate transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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 Ember Climate. 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 Ember Climate MCP in CrewAI

Agents share data through the crew memory. Once one agent retrieves a value, the others can act on it.

You use tool filtering to restrict access. A research agent gets generation tools, while a moderator gets emissions tools.

It is. You can use the multi-entity tool to grab data for several countries in one request, keeping your crew's execution time low.

You pass the server URL to your agent definition. The framework handles the connection and tool registration.

Every query is contained within your agent's session. We use zero-trust protocols to ensure your energy data remains private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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