Calculates organizational Scope 1, 2, and 3 emissions from financial exports and activity data using EPA emission factors.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
The install command below didn't complete successfully in our automated test.
uvx carbon-footprint-mcpDownloading cryptography (4.5MiB) Downloading pydantic-core (2.0MiB) Downloaded pydantic-core Downloaded cryptography Installed 29 packages in 60ms Traceback (most recent call last): File "/home/user/.cache/uv/archive-v0/ojJ6QRXIwFbFo8eT/bin/carbon-footprint-mcp", line 6, in <module> from carbon_footprint_mcp import mcp File "/home/user/.cache/uv/archive-v0/ojJ6QRXIwFbFo8eT/lib/python3.11/site-packages/carbon_footprint_mcp/__init__.py", line 1, in <module> from .server import mcp
This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 7d ago.
💡 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 Carbon Footprint Calculator.
Carbon Footprint Calculator MCP server calculates organizational greenhouse gas emissions from financial exports and structured operational data. It supports bank CSV files, Xero exports, QuickBooks Online exports, and directly supplied activity inputs. The resulting calculations cover Scope 1, Scope 2, and Scope 3 emissions.
The server helps associate transactions and activities with sources such as electricity, fuel, travel, shipping, waste, and refrigerants. When revenue or headcount data is provided, it can also calculate carbon-intensity scores. Results can be rendered as HTML and Markdown reports and written to a local output directory.
Emission factors come from the EPA GHG Emission Factors Hub, using the January 2025 release. The supported factor set includes eGRID 2023 electricity factors and IPCC AR5 global warming potentials.
Inputs are supplied as structured activity data or financial exports. The server maps relevant activity categories to available emission factors and calculates emissions across the three scopes. Electricity calculations use an EPA eGRID subregion, while other categories require details such as fuel type, quantity, travel mode, distance, material, or disposal method.
Supported examples include stationary and mobile combustion, refrigerant leakage, purchased electricity, purchased steam or heat, transportation and distribution, waste disposal, business travel, and employee commuting. The tool can list available fuel, electricity, and waste factors before calculations are performed.
The server operates entirely on the local machine or server. It does not send financial data to external APIs or cloud providers, and it does not store data by default. Its tools are read-only calculation and reporting operations.
Install uv, then add the server to an MCP client with the uvx carbon-footprint-mcp command. In Claude Desktop, the server can be configured with uvx as the command and carbon-footprint-mcp as its argument. The README also documents adding the same command through Claude Code or Cursor.
For local development, clone the repository, install it with pip install -e ., and run the carbon-footprint-mcp command. No API key, hosted account, or external service credential is listed as required.
computeEmissions(inputs_json) calculates greenhouse gas emissions from structured activity data across all three scopes.generateEmissionsReport(emissions_json, output_dir) creates HTML and Markdown reports and saves them to disk.listEmissionFactors(category) lists available fuel, eGRID, and waste emission factors.The electricity benchmarking model uses EPA eGRID regional factors, even though the workflow is intended for organizations in any country. Electricity inputs therefore require an eGRID subregion. Other categories also have specific required fields, such as gallons for mobile fuel, passenger-miles for travel, and short tons plus disposal method for waste.
The server provides calculations and reports rather than automated accounting validation or external data retrieval. Transaction categorization is described as assistance with identifying likely emission sources, so source data may still require review before being used in formal reporting. The project is released under the MIT license.
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