jagan-shanmugam/climatiq-mcp-server
FreeNot checkedA Model Context Protocol (MCP) server for accessing the Climatiq API to calculate carbon emissions. This allows AI assistants to perform real-time carbon calcul
About
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.
README
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.
Demo
https://github.com/user-attachments/assets/c253d6d1-ccf6-4c14-965e-6023ba2a0296
https://github.com/user-attachments/assets/d61c1181-acf6-4d9f-9a48-537fc64ac4c3
Features
This MCP server integrates with the Climatiq API to provide carbon emission calculations for AI assistants:
Tools
- set-api-key: Configure the Climatiq API key used for authentication
- electricity-emission: Calculate carbon emissions from electricity consumption
- travel-emission: Calculate carbon emissions from travel by car, plane, or train
- search-emission-factors: Search for specific emission factors in the Climatiq database
- custom-emission-calculation: Perform custom calculations using specific emission factors
- cloud-computing-emission: Calculate emissions from cloud computing resources usage
- freight-emission: Calculate emissions from freight transportation
- procurement-emission: Calculate emissions from procurement spending
- hotel-emission: Calculate emissions from hotel stays
- travel-spend: Calculate emissions from travel expenses
Resources
- Carbon calculation results are exposed as resources with a
climatiq://calculation/{id}URI scheme - Each resource contains detailed information about an emission factor and calculation results
Prompts
- climate-impact-explanation: Generate natural language explanations about the climate impact of specific emission calculations
Installation
From Source
This 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
Using uv
uv pip install climatiq-mcp-server
API Key Configuration
The server requires a Climatiq API key to function. You have several options to provide it:
Environment Variable: Set the
CLIMATIQ_API_KEYenvironment variable before starting the serverexport CLIMATIQ_API_KEY=your_climatiq_api_keyConfiguration During Installation:
CLIMATIQ_API_KEY=your_climatiq_api_key uv pip install climatiq-mcp-serverset-api-key Tool: Use the
set-api-keytool to configure it during runtime within the AI assistantConfiguration File: Create a
.envfile in the project directory:CLIMATIQ_API_KEY=your_climatiq_api_key
To get a Climatiq API key:
- Sign up at app.climatiq.io
- Follow the instructions at Getting API Keys
Running the Server
The server can be started directly from the command line:
climatiq-mcp-server
Setup in AI Assistants
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Configuration Example
"mcpServers": {
"climatiq-mcp-server": {
"command": "climatiq-mcp-server",
"env": {
"CLIMATIQ_API_KEY": "your_climatiq_api_key"
}
}
}
Examples and Utilities
Examples Directory
The examples/ directory contains:
- climatiq.ipynb: A Jupyter notebook demonstrating direct API usage with Climatiq
- simple_test.py: A simple utility for testing the API integration directly without MCP protocol
# Run the simple test
python examples/simple_test.py
Utility Scripts
The utils/ directory contains several helpful scripts:
Test Client
The test_client.py script tests all the tools, prompts, and resources:
python utils/test_client.py
LLM Example Client
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:
- Complete API wrapper with error handling and timeout management
- Resource and result caching to preserve calculation history
- Example prompts showing how to generate natural language explanations
- Demonstrates electricity emission, travel emission, and emission factor search capabilities
CLI Tool
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
Run MCP Server Script
Use the run_mcp_server.py script to directly run the server without installing:
python utils/run_mcp_server.py
Key Concepts
Activity IDs
An Activity ID is a key concept in Climatiq's API that groups similar emission factors together:
- Each emission factor in the Climatiq database has an activity ID
- Activity IDs group emission factors describing the same activity across regions, years, sources, etc.
- Examples:
electricity-supply_grid-source_residual_mix(electricity),passenger_vehicle-vehicle_type_car(car travel)
Calculation Methods
The Climatiq MCP server supports multiple calculation methods:
- Distance-based method for travel emissions
- Advanced travel calculations with origin-destination pairs
- Spend-based method for when you only have expenditure data
- Direct calculations using specific emission factors
Troubleshooting
API Key Issues
- Ensure
CLIMATIQ_API_KEYis set correctly in your environment or .env file - Verify the API key is active in your Climatiq dashboard
- Use
examples/simple_test.pyto check if your API key works correctly
Advanced Usage
For detailed documentation on using specific tools and advanced features, see the docs/README.md file.
About Climatiq
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.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Installing jagan-shanmugam/climatiq-mcp-server
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/jagan-shanmugam/climatiq-mcp-serverFAQ
Is jagan-shanmugam/climatiq-mcp-server MCP free?
Yes, jagan-shanmugam/climatiq-mcp-server MCP is free — one-click install via Unyly at no cost.
Does jagan-shanmugam/climatiq-mcp-server need an API key?
No, jagan-shanmugam/climatiq-mcp-server runs without API keys or environment variables.
Is jagan-shanmugam/climatiq-mcp-server hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install jagan-shanmugam/climatiq-mcp-server in Claude Desktop, Claude Code or Cursor?
Open jagan-shanmugam/climatiq-mcp-server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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