carbon-factor-matcher

MCP server for intelligent emission factor matching from ELCD and ecoinvent databases. Supports carbon accounting, LCA, and ESG reporting with AI-powered semantic search and 5-dimension data quality assessment.

该来源不提供完整文件导出（国内平台多为平台内托管），仅存元数据与原链

模型生成摘要（rules/v1 · 2026-09-27 16:35）：MCP server for intelligent emission factor matching from ELCD and ecoinvent databases
这是模型对公开材料的总结，不是官方声明，请以原链内容为准。

接入信息

传输形态: http
鉴权方式: 鉴权未知
端点: https://carbon-factor-matcher--nikeandocean.run.tools

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{
  "mcpServers": {
    "carbon-factor-matcher": {
      "url": "https://carbon-factor-matcher--nikeandocean.run.tools"
    }
  }
}

能力清单

工具	说明
factor_match	Intelligent emission factor matching for carbon accounting and Life Cycle Assessment (LCA). Takes a natural-language description of an industrial activity or material (e.g. '10kV industrial electricity in Guangdong, 2024' or 'polyethylene production') and returns the best-matching emission factor with CO2-equivalent intensity, confidence score, and reasoning. Free tier uses keyword search over ELCD database (~600 European factors). Pro tier adds embedding-based semantic search + LLM fine-ranking over ecoinvent (~21,000 global factors) with 5-dimension data quality assessment.
factor_search	Keyword search over emission factor databases. Returns matching factors with metadata including emission value (kgCO2e per unit), unit, geographic scope, source database, and publication year. Use this tool to browse available factors by material name, industry sector, or process type. Supports optional category filtering (e.g. 'electricity', 'fuel', 'transport', 'chemicals'). Free tier searches ELCD only; Pro tier searches all databases.
factor_detail	Retrieve full metadata for a specific emission factor by its unique identifier. Returns complete information including emission intensity value, unit, geographic scope, applicability conditions, data source, publication year, and (for Pro tier) 5-dimension data quality ratings covering technology representativeness, source reliability, geographic representativeness, time representativeness, and factor type.

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