WEB AI-Friendly

AI-Friendly Web Features

Our calculator is designed to work seamlessly with AI assistants, offering several features that make AI-powered workflows easy:

Shareable Pre-filled Links

AI agents can generate URLs with all calculation parameters encoded directly in the link. When users open these links, the calculator is automatically populated with all the data - ready to calculate instantly. Perfect for AI assistants to share personalized calculations.

Example: An AI can create a link like uteplennya.com/en/#state=eyJhcmVhIjoxNTAsLi4ufQ that opens the calculator with wall area, materials, and climate data already filled in.

JSON Export

After calculations, users can copy results in machine-readable JSON format. This allows AI assistants to process, analyze, or store the calculation data for further use.

CSV Export

Download calculation results as a CSV spreadsheet for easy import into Excel, Google Sheets, or other data analysis tools. All headers are properly localized.

MCP API

What is MCP?

Model Context Protocol (MCP) is a standard that allows AI assistants like Claude, ChatGPT, and others to connect to external tools and services.

Our calculator exposes an MCP server that enables AI agents to perform insulation calculations, compare materials, and generate detailed reports automatically.

Available Tools

AI agents can use the following tools when connected to our calculator:

get_insulation_materials()

Returns available insulation materials (mineral wool, EPS, XPS, polyurethane) with their thermal properties and costs.

get_climate_data(region)

Returns heating season climate data for specified regions with monthly temperatures and heating days.

calculate_insulation(...)

Performs full insulation calculations for thicknesses from 20-200mm, returning energy savings, costs, and payback periods.

generate_insulation_report(...)

Generates detailed reports with cost breakdowns, thermal analysis, and 10-year savings projections.

How to Connect

AI agents can connect to our MCP server using the STDIO transport protocol.

Claude Desktop Configuration

Add the following to your claude_desktop_config.json file:

{
  "mcpServers": {
    "insulation-calculator": {
      "command": "python",
      "args": ["/path/to/mcp_server.py"]
    }
  }
}

Other MCP-Compatible Agents

Run the MCP server using STDIO transport:

python mcp_server.py

Example Usage

Once connected, you can ask your AI assistant questions like:

"Calculate insulation needs for a 150 m² brick wall. The wall is 38cm brick. I want 20°C inside, gas heating efficiency 0.9, energy cost 2.64 UAH/kWh. Compare mineral wool vs EPS."

The AI agent will automatically use our calculator to provide complete analysis with savings, costs, and recommendations.

Getting Started

1

Clone or download the MCP server

Get mcp_server.py from our repository

2

Configure your AI agent

Add the server to your agent's MCP configuration

3

Start calculating

Ask your AI assistant to make insulation calculations

AI Agent Integration