MCP server for calculating carbon emissions through the Climatiq API across travel, electricity, cloud, freight, and spending activities.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
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๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Climatiq MCP Server.
set-api-keyConfigure the Climatiq API key used for authentication
electricity-emissionCalculate carbon emissions from electricity consumption
travel-emissionCalculate carbon emissions from travel by car, plane, or train
search-emission-factorsSearch for specific emission factors in the Climatiq database
custom-emission-calculationPerform custom calculations using specific emission factors
cloud-computing-emissionCalculate emissions from cloud computing resources usage
A Model Context Protocol (MCP) server for accessing the Climatiq API to calculate carbon emissions. This allows AI assistants to perform real-time carbon calculations and provide climate impact insights.
https://github.com/user-attachments/assets/c253d6d1-ccf6-4c14-965e-6023ba2a0296
https://github.com/user-attachments/assets/d61c1181-acf6-4d9f-9a48-537fc64ac4c3
This MCP server integrates with the Climatiq API to provide carbon emission calculations for AI assistants:
climatiq://calculation/{id} URI schemeThis project uses uv for virtual environment and dependency management. Make sure to install uv first.
The server requires a Climatiq API key to function. You have several options to provide it:
Environment Variable: Set the CLIMATIQ_API_KEY environment variable before starting the server
Configuration During Installation:
set-api-key Tool: Use the set-api-key tool to configure it during runtime within the AI assistant
Configuration File: Create a .env file in the project directory:
To get a Climatiq API key:
The server can be started directly from the command line:
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
The examples/ directory contains:
The utils/ directory contains several helpful scripts:
The test_client.py script tests all the tools, prompts, and resources:
The llm_example_client.py script demonstrates how a Large Language Model (like Claude) could interact with the Climatiq MCP server:
Key features:
A command-line interface tool for direct API access without the MCP server complexity:
Use the run_mcp_server.py script to directly run the server without installing:
An Activity ID is a key concept in Climatiq's API that groups similar emission factors together:
electricity-supply_grid-source_residual_mix (electricity), passenger_vehicle-vehicle_type_car (car travel)The Climatiq MCP server supports multiple calculation methods:
CLIMATIQ_API_KEY is set correctly in your environment or .env fileexamples/simple_test.py to check if your API key works correctlyFor detailed documentation on using specific tools and advanced features, see the docs/README.md file.
Climatiq provides a powerful API for carbon intelligence, allowing you to calculate emissions from electricity usage, transportation, procurement, and more. This MCP server makes those capabilities accessible to AI assistants through the Model Context Protocol.
For more information about Climatiq, visit climatiq.io.
This project is licensed under the MIT License - see the LICENSE file for details.
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