How to Use the Electricity Maps Carbon Intelligence MCP in AutoGen

Q: How do I load the Electricity Maps Carbon Intelligence into AutoGen?

Install the autogen-extmcp package. Initialize mcpservertools with your endpoint URL and pass the resulting tool list directly into your AssistantAgent constructor.

Q: How does AutoGen handle the API schema conversion for Electricity Maps Carbon Intelligence?

The McpToolAdapter translates the server's tool definitions into a format your agents understand. You never write manual JSON schema wrappers for the grid endpoints.

Give your AutoGen agents live grid data via this MCP integration to debate workload placement based on carbon intensity.

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Connect Electricity Maps Carbon Intelligence MCP to AutoGen

Create your Vinkius account to connect Electricity Maps Carbon 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 Electricity Maps Carbon Intelligence with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate carbon intensity costs

The `get_carbon_intensity` tool feeds real-time regional emissions data straight into your multi-agent conversations via the MCP protocol. A sustainability agent queries the API to find the exact carbon footprint of a specific data center zone. This creates hard constraints for your system. While a performance agent argues for routing a job to the closest server, the sustainability agent uses the live CO2 metrics to push back and negotiate a greener alternative.

Analyze generation sources

The `get_power_production_breakdown` tool forces your AI client to look at the actual physics of the grid. It returns the exact megawatt split between renewables and fossil fuels currently powering a region. Your agents stop relying on generic assumptions about green energy. They parse the live drop in solar output during the evening and actively debate whether to delay a batch processing job until wind generation picks up.

Define the MCP Server boundaries

The `list_energy_zones` tool provides the exact list of geographic regions the agents are allowed to analyze. Your system calls this endpoint to establish the playing field before the debate even starts. Agents use this directory to map out their options. If they need to shift a workload out of a high-carbon zone, they cross-reference this list to find valid alternative regions.

Setup guide

Set up Electricity Maps Carbon 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 Electricity Maps Carbon 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="Electricity Maps Carbon Intelligence_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Electricity Maps Carbon 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="Electricity Maps Carbon Intelligence_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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 Electricity Maps. 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 Electricity Maps Carbon Intelligence MCP in AutoGen

Install the `autogen-ext[mcp]` package. Initialize `mcp_server_tools` with your endpoint URL and pass the resulting tool list directly into your `AssistantAgent` constructor.

Yes. You attach the tool list to any agent that needs grid visibility. They can independently query different regions and bring conflicting data points back to the group chat.

The `McpToolAdapter` translates the server's tool definitions into a format your agents understand. You never write manual JSON schema wrappers for the grid endpoints.

That is the entire point of the framework. One agent might prioritize low carbon intensity while another looks at the power breakdown to avoid unstable wind generation. They debate until they reach your defined consensus threshold.

The integration strictly reads public environmental data based on region codes. The server has zero access to your internal agent prompts, conversation histories, or workload routing logic.

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