openLCA MCP Server

openLCA MCP Server

An MCP (Model Context Protocol) server that connects AI assistants to a running openLCA instance. Developed and tested with Claude Desktop; compatible with any MCP client that supports stdio transport. Built by Below280, the UK partner for openLCA.

The server exposes 31 tools covering the full LCA workflow: exploring databases, building and editing models, running calculations (scenarios, sensitivity, Monte Carlo, contribution analysis), auditing and validating models, and extracting data quality assessments. All calculation patterns are tested against production ecoinvent databases.

The server works with both ecoinvent-family databases (ecoinvent, EN15804GD, HiQLCD, BAFU) and FLCAC-family databases (LCA Commons, US LCI, USEEIO). It asks which family you are using, or auto-detects from the flow property names.

Available on PyPI and the MCP Registry.

Install

Quick setup (PyPI)

pip install b280-olca-mcp

This installs the server and its dependencies (mcp, olca-ipc) in one step. The server runs from anywhere with python -m b280olcamcp.

Development setup (GitHub)

Clone the repository for the latest code, the React dashboard, or if you want to modify the server:

git clone https://github.com/Below280/B280-olca-MCP.git
cd B280-olca-MCP
pip install -r requirements.txt

The server entry point is b280olcamcp/server.py.

What it does

Someone using this MCP can say things like:

• 'Make me a model with 34 kWh UK electricity, 5 kg sodium hydroxide, and 34 kWh steam'
• 'Build an EPD model from this LCI'
• 'Run two scenarios, one with transport at 100 km and one at 500 km'
• 'Which processes contribute most to climate change in my system?'
• 'Vary the electricity and PET resin parameters by 10%'
• 'Validate my product system and check if the linking is correct'
• 'Run 1000 Monte Carlo iterations and show me the uncertainty'
• 'Help me connect to openLCA from R / Go / Rust'
• 'What can you do?' (the help tool)

The AI assistant handles the conversation, builds the tool calls, and presents results visually with charts, tables, and exportable data.

Connect your MCP client

The server uses stdio transport. Any MCP client that can spawn a local Python process will work.

Claude Desktop

In Claude Desktop, go to Settings > Developer > Edit Config. Add an openLCA entry to the mcpServers section.

If you installed via PyPI:

{
  "mcpServers": {
    "openLCA": {
      "command": "python",
      "args": ["-m", "b280_olca_mcp"],
      "env": {
        "OLCA_PORT": "8080"
      }
    }
  }
}

If you cloned from GitHub:

{
  "mcpServers": {
    "openLCA": {
      "command": "python",
      "args": ["C:/path/to/B280-olca-MCP/b280_olca_mcp/server.py"],
      "env": {
        "OLCA_PORT": "8080"
      }
    }
  }
}

On Windows, if Claude Desktop cannot find Python, use the full path to your Python executable.

Restart Claude Desktop after saving.

Cursor

Go to Settings > Tools & MCP > Add MCP Server. Choose stdio transport, set the command to python and the argument to -m b280olcamcp (PyPI) or the path to b280olcamcp/server.py (GitHub clone). Cursor picks up config changes without restarting.

VS Code

Add the server to .vscode/mcp.json in your workspace or user settings:

{
  "servers": {
    "openLCA": {
      "type": "stdio",
      "command": "python",
      "args": ["-m", "b280_olca_mcp"],
      "env": {
        "OLCA_PORT": "8080"
      }
    }
  }
}

Note: VS Code uses servers as the root key, not mcpServers. If using GitHub Copilot, switch Copilot Chat to Agent mode.

ChatGPT

Shortened. The full README is on GitHub.