MCP 服务器

carbon-factor-matcher

Enables carbon accounting by matching activities to emission factors via semantic search and AI ranking, supporting ELCD and ecoinvent databases.

README

Carbon Factor Matcher — MCP Server for Carbon Accounting

An MCP (Model Context Protocol) server that connects LLMs with carbon footprint databases. It provides intelligent emission factor matching for carbon accounting, LCA (Life Cycle Assessment), and ESG reporting applications.

What is this MCP?

Carbon Factor Matcher helps AI agents and LLM-based applications find the most appropriate emission factors from standardized environmental databases. It uses a two-stage hybrid search algorithm:

Embedding-based rough filtering — Semantic similarity to find candidate factors
LLM-based fine ranking — AI-powered selection with reasoning and confidence scores

Supported Databases

ELCD — European Reference Life Cycle Database (included)
ecoinvent 3.10 — Swiss Centre for Life Cycle Inventories (Pro license required)

Key Features

5-dimension data quality rating (technology, geography, source, time, factor type)
Multi-language support (Chinese/English activity descriptions)
MCP-compatible — works with Claude, Cursor, and any MCP client

Installation

Add to your MCP settings (claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "carbon-factor-matcher": {
      "command": "npx",
      "args": ["-y", "@nikeandocean/carbon-factor-matcher"],
      "env": {
        "CARBON_FACTOR_LICENSE_KEY": "your-license-key",
        "LLM_API_KEY": "your-api-key",
        "LLM_BASE_URL": "https://api.deepseek.com",
        "LLM_MODEL": "deepseek-chat"
      }
    }
  }
}

Pricing

This is a commercial MCP server. You can purchase the access license key via PayPro Global.

Plan	Price	Features
Free	$0	ELCD database, basic search, top 3 results
Pro	$5 (one-time)	ELCD + ecoinvent, hybrid matching, unlimited results, data quality rating

Purchase License Key

👉 Buy Pro License on PayPro Global

After purchase, you will receive a license key via email. Set it as the CARBON_FACTOR_LICENSE_KEY environment variable.

Configuration

Variable	Description	Default
`CARBON_FACTOR_LICENSE_KEY`	Your license key (empty = Free tier)	—
`LLM_API_KEY`	LLM API key (DeepSeek/OpenAI)	—
`LLM_BASE_URL`	LLM endpoint URL	`https://api.deepseek.com`
`LLM_MODEL`	LLM model name	`deepseek-chat`
`CARBON_FACTOR_DATA_DIR`	Path to factor database	`data/factors`

Available Tools

`factor_match`

Match activity data to the best emission factor using semantic search.

Input:

{
  "activity_data": "Factory in Shenzhen, 10kV industrial electricity, 2024, semiconductor fab",
  "top_k": 10
}

Output:

{
  "selected_factor": {
    "id": "elec-cn-south-10kv-2024",
    "name": "Electricity, 10kV, South China Grid",
    "value": 0.6101,
    "unit": "kgCO2e/kWh"
  },
  "confidence": 0.92,
  "reason": "Best match for industrial electricity in South China region",
  "alternatives": [...]
}

`factor_search`

Search emission factors by keyword with optional filters.

Input:

{
  "query": "diesel",
  "category": "fuel",
  "limit": 10
}

`factor_detail`

Get full metadata for a specific factor.

Input:

{
  "factor_id": "elec-cn-south-10kv-2024"
}

System Requirements

Python 3.11+
LLM API key (DeepSeek recommended, or any OpenAI-compatible endpoint)
2GB+ RAM for embedding model

Tech Stack

MCP SDK — Model Context Protocol implementation
Sentence Transformers — Semantic embedding (shibing624/text2vec-base-chinese)
DeepSeek/OpenAI — LLM-based factor ranking
SQLite — Usage tracking
Python 3.11+ — Runtime