Electricity Maps Carbon Intelligence MCP for AI. Analyze carbon footprint and power mix for any global zone.
Works with every AI agent you already use
…and any MCP-compatible client








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Electricity Maps Carbon Intelligence provides real-time global energy data, letting your AI agent understand a zone's power mix and carbon footprint instantly.
Get immediate metrics like gCO2eq/kWh and the percentage of renewables for over 100 countries and regions. This tool lets you analyze environmental impact without manually checking multiple utility websites.
What your AI can do
Get carbon intensity
Retrieves the current carbon emission rate (gCO2eq/kWh) for a specific geographical zone.
Get power production breakdown
Provides a detailed list of energy sources, such as solar and gas, currently powering a specified zone.
List energy zones
Outputs all geographical regions for which the system can retrieve energy data metrics.
Get the current carbon emission rate (gCO2eq/kWh) for any specified country or region.
Determine exactly what energy types—like wind, nuclear, or coal—are currently contributing to a specific grid's power supply.
Find out the current proportion of clean energy sources within a given region’s overall power generation.
Retrieve a full list of all geographical regions for which energy metrics are currently available.
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Electricity Maps Carbon Intelligence: 3 Tools
Analyze, map, and compare real-time energy metrics by running these three specialized tools in your AI client.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Electricity Maps Carbon Intelligence on VinkiusGet Carbon Intensity
Retrieves the current carbon emission rate (gCO2eq/kWh) for a specific geographical zone.
Get Power Production Breakdown
Provides a detailed list of energy sources, such as solar and gas, currently...
List Energy Zones
Outputs all geographical regions for which the system can retrieve energy data...
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Make Your AI Do More
Start with Electricity Maps Carbon Intelligence, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Tracking global energy impact used to mean cross-referencing dozens of websites.
To figure out a region’s environmental cost, you used to open five different national utility sites. You'd check one for the current carbon rate, another for the renewable percentage, and a third just to confirm the zone code. Then, you copied those three data points into a spreadsheet, cross-referencing dates manually.
With this MCP, your agent does it in seconds. Instead of manual logins and copy-pasting, you ask one question—'What is the carbon intensity and mix for Brazil?'—and get all the key metrics returned instantly.
Electricity Maps Carbon Intelligence: Getting Source Detail
The biggest manual step that disappears is having to assume why a zone has a certain carbon rate. Instead of accepting a single gCO2eq/kWh number, you can now ask for the source breakdown using `get_power_production_breakdown`. This tells you if the low carbon score comes from massive hydropower or something else entirely.
You stop treating global energy data like a black box. You start seeing the actual inputs—solar, wind, coal—and understanding exactly what drives the final number.
What your AI can actually do with this
This connector equips your AI client with deep, real-time energy intelligence. You can ask questions about global power grids—like finding out a specific region's carbon intensity or seeing what sources are powering it right now. Your agent pulls the current gCO2eq/kWh rating and provides a detailed breakdown of the grid mix, showing you if solar, wind, or coal is dominating.
If you’re auditing emissions for a global operation, comparing zones to find the lowest impact, or just researching energy transitions, this MCP acts as your dedicated analyst. It pulls all that data into one conversation thread, making it part of the Vinkius catalog you rely on.
019d8433-5bd6-738a-ac47-7ee6b537b43b Here's how it actually works
The bottom line is you get a single, conversational feed of complex global energy metrics.
First, connect your AI client to this MCP and supply the required Electricity Maps API Key.
Then, ask your agent a specific question, like 'What is the carbon intensity in Germany?' or 'Show me the power mix for France.'
The system returns the precise data points—the carbon rate, the source breakdown, or the list of available zones—directly into your chat window.
Who is this actually for?
This MCP is for technical professionals who deal with environmental compliance or infrastructure planning. Think of the sustainability manager staring at mountains of regional reports, or the cloud engineer trying to justify a data center move based on local energy impact.
Auditing corporate emissions by comparing the carbon footprint across global operational sites.
Optimizing server workloads or data center placement based on real-time local grid intensity and renewable availability.
Tracking the historical and current performance of national energy transitions across different zones.
What Changes When You Connect
Instantly audit emissions. Use get_carbon_intensity to check the precise gCO2eq/kWh rating for a location, allowing you to compare multiple sites in minutes instead of hours.
Optimize infrastructure decisions. When planning data center moves, your agent pulls the real-time power source mix via get_power_production_breakdown, helping you select grids with low-carbon inputs.
Benchmark regions globally. By combining list_energy_zones and subsequent calls to other tools, you can systematically compare environmental impact across dozens of countries for quarterly reporting.
Track renewable progress. You get the current percentage of clean energy sources in a zone’s power mix, making it easier to report on sustainability goals.
Simplify complex data retrieval. Instead of logging into multiple national utility websites, your agent handles the API calls using this MCP.
See it in action
Determining optimal cloud placement
A Cloud Engineer needs to move a compute cluster but can't find one with low carbon impact. They ask their agent, and it uses list_energy_zones to narrow down options, then runs get_power_production_breakdown on those zones to confirm high renewable input before running the final check via get_carbon_intensity.
Writing a regional sustainability report
A Sustainability Manager needs to compare three different European regions. They ask their agent, and it pulls data for all three zones simultaneously, comparing not just the overall carbon rate (get_carbon_intensity) but also detailing which specific energy source (e.g., nuclear vs. hydro) is driving that number.
Analyzing grid transition risks
A Policy Researcher needs to track how national grids are shifting away from coal. They use the MCP to list available zones, select several industrial nations, and then run a breakdown check (get_power_production_breakdown) on each one to see if fossil fuels are declining in the mix.
Selecting energy-intensive appliances
An Eco-conscious Consumer wants to know when it’s safest to run a large, power-hungry appliance. They ask their agent for the current carbon intensity of their zip code and get an immediate rating that tells them if running the machine now is environmentally responsible.
The honest tradeoffs
Searching general web articles
A user searches 'carbon footprint of France' on Google and gets a mix of 2019 reports, academic papers, and press releases. The data is old or incomplete.
Ask your agent to use the Electricity Maps Carbon Intelligence MCP. First run list_energy_zones to confirm the zone code, then immediately ask for get_carbon_intensity to get current, real-time metrics.
Relying on single data points
A developer only checks the carbon intensity and assumes that’s enough. They miss out on knowing why the carbon rate is low.
Always pair get_carbon_intensity with get_power_production_breakdown. This shows you not just the number, but the actual sources making up the grid.
Guessing available zones
A user assumes a country is supported and tries to query it. The API fails with an unknown error because they don't know the correct zone ID.
Always start by calling list_energy_zones. This confirms that the data provider supports your target region before you spend time querying metrics.
When It Fits, When It Doesn't
Use this MCP if your primary need is a standardized, real-time assessment of energy sources and environmental impact across different geographical zones. It excels at profiling: 'What is X's carbon rate?' or 'What makes up Y's power mix?'. Don't use it if you need predictive modeling; the data provided is static for any given moment in time, not a time-series forecast (e.g., predicting energy needs based on next week’s weather). For historical analysis spanning years, you will need a dedicated archive service. If your goal is complex load forecasting or balancing supply against predicted demand, this MCP provides the inputs but isn't the final modeling tool.
Questions you might have
How do I use get_carbon_intensity with Electricity Maps Carbon Intelligence? +
You tell your agent which zone you need data for. It runs get_carbon_intensity and gives you the current carbon emission rate in gCO2eq/kWh.
Is get_power_production_breakdown real-time? +
Yes, it provides a breakdown of energy sources currently contributing to the grid. It details percentages and types like wind or nuclear power.
Do I need to know all zones before using list_energy_zones? +
No. Calling list_energy_zones first gives you a complete catalog of supported regions, so you can pick your targets without guessing the required zone code.
What if I need to compare two zones' carbon intensity? +
You simply ask your agent for both. It calls get_carbon_intensity twice—once for each location—and presents a direct comparison in one response.
What happens if I run into an authentication error when calling get_carbon_intensity? +
First, verify your API key credentials. The agent requires a valid and active key provided by Electricity Maps. If the error persists, ensure the key was correctly entered in Vinkius and has not expired or been revoked.
How often do the metrics update for get_power_production_breakdown? +
The data reflects near real-time grid conditions. While it's not instantaneous, the system updates frequently enough to support operational planning and sustainability auditing across major grids.
If I use list_energy_zones and then try get_carbon_intensity with a bad code, what error do I get? +
The agent will report an invalid input or zone not found error. This means the specific code you provided doesn't match any defined energy region in the current dataset.
Can my AI client optimize calls for many locations using get_carbon_intensity? +
Yes, your agent can process multiple zones sequentially within a single workflow. You retrieve the list of codes via list_energy_zones and then loop through them to build a comprehensive report.
Can I check the carbon intensity in Brazil? +
Yes! Use the get_carbon_intensity tool with the zone code 'BR'. It will return the latest gCO2eq/kWh for the Brazilian grid.
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