Računalničar, Sebastijan Bandur s.p.
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How to generate quotes with an AI agent — and why the model must not price them

An increasingly common wish: “I want to describe a job in Claude Desktop and get a quote.” It's doable — but only if a tool computes the price, not the language model. Here's how.

A quote document and a price list as the calculation tool

We keep hearing the same wish from small make-to-order businesses — joinery, metalwork, installations: “I want to describe a job in Claude Desktop (or ChatGPT) and get a quote.” Picture a joinery that builds custom windows and doors: the owner would like to dictate “three wooden windows 120×140, double glazing, one fire door” and get a finished quote.

It's doable. But there's a trap that separates a useful solution from an expensive mistake.

The trap: the model must not price things

A language model is great at confidently guessing. Ask it to “estimate” the price of a window and it will give you a tidy number — often a wrong one. In quoting, a wrong price isn't a typo; it's a lost deal or a loss on the deal.

The rule is simple: the AI gathers parameters and writes the text, but a tool computes the price — deterministically, from your price list. Same result every time, verifiable.

The solution: an MCP connector for quotes

Between Claude Desktop and your price list we put an MCP connector — a small server with a few tools:

  • calculate_quote — input is the line items (type, dimensions, material, glazing, quantity, options); output is priced line items and a total (with and without VAT). Your rules do the math, not the model.
  • create_quote — saves the quote, assigns a number and returns a PDF with your logo, terms and validity.
  • optionally customers — a simple directory for repeat clients.

The flow: you describe the job in Claude Desktop → the agent calls calculate_quote, then create_quote → it returns a PDF and a number. No new app to build and learn.

The hardest part is your price list

Honestly: the AI layer is the easy part. The value and most of the work are in digitising the pricing logic. If your price list is in a spreadsheet, great. If it's “in the master's head,” the first step is to capture it into rules — and that's the biggest benefit of the project, AI aside.

A draft, not blind automation

For make-to-order work the agent prepares a draft quote that a human approves. Measurements and feasibility stay with the craftsperson; AI removes the typing, the math and the formatting, not the judgement.

Customer data is processed in the EU (GDPR), behind a secure token.

The result

A quote produced in a minute instead of half an hour, consistent, numbered and stored. It's a concrete example of our AI integration service: we wire AI into your existing process rather than sell you another tool.

More about AI for business ↗ · MCP connectors ↗

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