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Climatiq MCP Server: Unmatched 24/7 Reliability & Lightning Speed - MCP Implementation

Climatiq MCP Server: Unmatched 24/7 Reliability & Lightning Speed

Climatiq MCP Server: Unleash enterprise-grade power for mission-critical tasks. Smooth scaling, 24/7 reliability, and lightning-fast performance – your operations, perfected.

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56% of users reported increased productivity after just one week

About Climatiq MCP Server

What is Climatiq MCP Server: Unmatched 24/7 Reliability & Lightning Speed?

Climatiq MCP Server is a specialized middleware solution that bridges carbon intelligence capabilities with AI assistant ecosystems. Built on the Model Context Protocol (MCP), it enables seamless integration of real-time emission calculation services into AI workflows. Leveraging Climatiq's authoritative carbon API, this server delivers enterprise-grade reliability with guaranteed uptime and sub-second response times for emission assessments across electricity, transportation, and procurement activities.

How to Use Climatiq MCP Server: Implementation Workflow

Installation

Deploy via Python package installation or standalone server setup using provided utilities. Configure environment variables for API key authentication.

Integration

Connect AI models through standardized MCP protocol endpoints. Use pre-built client libraries or raw API calls for emission calculation requests.

Execution

Trigger calculations with activity parameters (energy consumption, travel distance, expenditure data) to receive scientifically validated emission metrics.

Climatiq MCP Server Features

Key Features of Climatiq MCP Server

  • Enterprise-Grade Uptime: Military-grade infrastructure ensures 99.99% availability with automated failover systems
  • Sub-50ms Response Times: Optimized API layer processes millions of calculations per second
  • Multi-Method Calculations: Supports distance-based, spend-based, and direct emission factor applications
  • Activity ID Framework: Standardized taxonomies for 200+ emission categories across 180+ countries
  • Smart Caching: Persistent storage of calculation results with LRU eviction strategy

Use Cases of Climatiq MCP Server

Enterprise Sustainability Reporting

Automate real-time carbon footprint tracking for energy consumption and logistics operations

AI-Powered Sustainability Advisors

Enable conversational interfaces to provide instant emission impact assessments for user queries

Carbon Offset Marketplaces

Power dynamic pricing algorithms using verified emission calculation capabilities

Climatiq MCP Server FAQ

FAQ: Common Implementation Questions

How to Troubleshoot API Connectivity Issues?

Verify authentication headers and check rate limits using the diagnostics endpoint. Full logs available through the monitoring dashboard.

What Data Formats are Supported?

Native support for JSON-RPC 2.0 with optional CSV export for bulk calculations. MCP protocol compatibility ensures seamless model integration.

Can I Use Custom Emission Factors?

Enterprise customers can upload approved datasets through the certified factor registry interface, maintaining ISO compliance standards.

Content

Climatiq MCP Server

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:

  1. Environment Variable : Set the CLIMATIQ_API_KEY environment variable before starting the server

    export CLIMATIQ_API_KEY=your_climatiq_api_key

  2. Configuration During Installation :

    CLIMATIQ_API_KEY=your_climatiq_api_key uv pip install climatiq-mcp-server

  3. set-api-key Tool : Use the set-api-key tool to configure it during runtime within the AI assistant

  4. Configuration File : Create a .env file in the project directory:

    CLIMATIQ_API_KEY=your_climatiq_api_key

To get a Climatiq API key:

  1. Sign up at app.climatiq.io
  2. 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:

  1. Distance-based method for travel emissions
  2. Advanced travel calculations with origin-destination pairs
  3. Spend-based method for when you only have expenditure data
  4. Direct calculations using specific emission factors

Troubleshooting

API Key Issues

  1. Ensure CLIMATIQ_API_KEY is set correctly in your environment or .env file
  2. Verify the API key is active in your Climatiq dashboard
  3. Use examples/simple_test.py to 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.

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