How to Use the Electricity Maps Carbon Intelligence MCP in LangChain

Q: How do I connect the Electricity Maps Carbon Intelligence MCP Server to LangChain?

Install langchain-mcp-adapters. Use MultiServerMCPClient with the server URL and pass client.gettools() to your ReAct agent.

Build carbon-aware reasoning pipelines with LangChain by pulling live grid data via this MCP Server.

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Connect Electricity Maps Carbon Intelligence MCP to LangChain

Create your Vinkius account to connect Electricity Maps Carbon Intelligence to LangChain 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 LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Route workloads via LangChain

The `get_carbon_intensity` tool feeds live grid emissions data straight into your agent's decision loop. You pass a zone code like FR or US-CA, and your AI client reads the exact grams of CO2 per kilowatt-hour currently generated. This isn't historical data. Your ReAct agent pulls this metric, compares it across regions, and decides where to execute compute-heavy tasks. You track every API call and token spent right inside LangSmith.

Analyze live grid generation

The `get_power_production_breakdown` tool tells your agent exactly what physical resources are powering a specific zone right now. If wind generation drops in Texas, your script sees the spike in natural gas usage immediately. You chain this output into downstream analytics or reporting tools. The agent parses the megawatt split between nuclear, solar, and coal, formatting the raw JSON into actionable alerts before passing it to the next link in your workflow.

Map available MCP Server regions

The `list_energy_zones` tool gives your agent the complete directory of supported global grid territories. Your script queries this endpoint to build a dynamic list of valid targets before running any heavy analytics. Instead of hardcoding region codes, your LangChain setup stays flexible. The agent fetches the active zones, filters them based on your custom logic, and proceeds to map out carbon costs across the globe.

Setup guide

Set up Electricity Maps Carbon Intelligence MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Electricity Maps Carbon Intelligence tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "electricity-maps-carbon-intelligence-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Electricity Maps Carbon Intelligence transactions"
    })
    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 LangChain

Install `langchain-mcp-adapters`. Use `MultiServerMCPClient` with the server URL and pass `client.get_tools()` to your ReAct agent.

Yes. Once connected, your agent decides when to call the grid API based on the user prompt. It handles the zone mapping and data retrieval without manual intervention.

Your chain will throw an error if you hit the endpoint too hard. You need to build retry logic or fallback chains directly into your script to handle timeouts gracefully.

Enable LangSmith in your environment. It traces every tool invocation, showing you exactly what the agent sent to the MCP Server and how long the grid API took to respond.

This server only processes public grid telemetry and region codes like US-CA. It never touches user PII, proprietary source code, or internal database credentials. Your connection remains strictly focused on global power metrics.

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