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.
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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.
# Clone the repository
git clone https://github.com/your-org/climatiq-mcp-server.git
cd climatiq-mcp-server
# Create a virtual environment
uv venv
# Activate the virtual environment
# On macOS/Linux:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate
# Install dependencies with development extras
uv sync --dev --extra all
uv pip install climatiq-mcp-server
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
export CLIMATIQ_API_KEY=your_climatiq_api_key
Configuration During Installation:
CLIMATIQ_API_KEY=your_climatiq_api_key uv pip install climatiq-mcp-server
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:
CLIMATIQ_API_KEY=your_climatiq_api_key
To get a Climatiq API key:
The server can be started directly from the command line:
climatiq-mcp-server
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
"climatiq-mcp-server": {
"command": "climatiq-mcp-server",
"env": {
"CLIMATIQ_API_KEY": "your_climatiq_api_key"
}
}
}
The examples/
directory contains:
# Run the simple test
python examples/simple_test.py
The utils/
directory contains several helpful scripts:
The test_client.py
script tests all the tools, prompts, and resources:
python utils/test_client.py
The llm_example_client.py
script demonstrates how a Large Language Model (like Claude) could interact with the Climatiq MCP server:
python utils/llm_example_client.py
Key features:
A command-line interface tool for direct API access without the MCP server complexity:
# For electricity emissions
python utils/climatiq_cli.py electricity --energy 1000 --unit kWh --region US
# For travel emissions
python utils/climatiq_cli.py travel --mode car --distance 100 --unit km --region US
Use the run_mcp_server.py
script to directly run the server without installing:
python utils/run_mcp_server.py
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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