Tri‑Tender Pricing MCP

This is a production‑ready Model Context Protocol (MCP) server built with FastMCP for Tri‑Tender. It focuses on pricing schedules for tenders and RFQs.

The server exposes tools that:

1. Detect and extract pricing requirements from tender packs

2. Build a structured pricing model from tender rules + company rates

3. Calculate final prices (including markups & VAT)

4. Optionally compare against market prices

5. Generate a styled HTML pricing report ready for PDF export

6. Wrap the output in a Tri‑Tender‑friendly format for preview

1. Project Structure

tri_tender_pricing_mcp/
├── server.py
├── requirements.txt
├── README.md
├── tools/
│   ├── extract_pricing_requirements.py
│   ├── build_pricing_model.py
│   ├── calculate_prices.py
│   ├── generate_html_report.py
│   ├── fetch_market_prices.py
│   └── format_output.py
├── utils/
│   ├── pdf_reader.py
│   ├── docx_reader.py
│   ├── xlsx_reader.py
│   ├── classify_document.py
│   └── clean_text.py
└── resources/
    ├── pricing_templates/
    │   ├── base_template.html
    │   ├── table_style.css
    │   └── branding.css
    └── sample_data/
        └── example_pricing.json

Related MCP server: TenderAI

2. Installation

Create and activate a virtual environment (recommended), then:

pip install -r requirements.txt

Verify that FastMCP is installed:

fastmcp version

3. Running the MCP Server

fastmcp run server.py

By default FastMCP will use stdio for transport. Some hosts also support:

python server.py

or

fastmcp run --transport sse --host 0.0.0.0 --port 8000 server.py

(Consult the FastMCP docs / your host's docs if you want SSE or HTTP.)

4. Registering in Tri‑Tender (Desktop / Dyad)

Use a configuration entry like this in your MCP client:

{
  "mcpServers": {
    "tri_tender_pricing_mcp": {
      "command": "python",
      "args": ["server.py"],
      "env": {}
    }
  }
}

If you deploy it remotely with SSE/HTTP, you can instead use:

{
  "mcpServers": {
    "tri_tender_pricing_mcp": {
      "url": "http://YOUR-HOST:8000/sse"
    }
  }
}

5. Exposed Tools

detect_pricing_requirements(file_path: str) -> dict

• Reads PDF, DOCX or XLSX

• Cleans the text

• Classifies the document type (tender, pricing schedule, BOQ, etc.)

• Tries to extract pricing‑related sections

• Returns:

  • instructions (LLM‑ready description of what was found)

  • summary

  • currency

  • pricing_items (rough skeleton list)

  • raw_text (trimmed excerpt for the LLM)

build_model(description: str, tender_rules: str, company_rates: str) -> dict

• Takes free‑text input and produces a structured pricing model with:

  • items: description, unit, quantity, base_rate, markup_percent

  • meta: currency, VAT %, assumptions

calculate(model_json: dict) -> dict

• Applies line‑level calculations:

  • line_total_ex_vat

  • line_vat_amount

  • line_total_inc_vat

• Sums to grand totals

• Returns items + totals + instructions for the LLM.

market_prices(item_name: str) -> dict

• Currently returns simulated market prices.

• Designed to be extended with real HTTP APIs (hardware, fuel, etc.).

render_report(pricing_data: dict) -> dict

• Renders a styled HTML report based on resources/pricing_templates/base_template.html

• Returns: { "mime_type": "text/html", "html": "..." }

final_output(html: str) -> dict

• Final simple wrapper used by Tri‑Tender desktop app / Dyad templates.

6. Customisation

• Update resources/pricing_templates/base_template.html and CSS files to match Tri‑Tender branding.

• Extend the logic in calculate_prices.py to support:

  • multi‑year escalations

  • different markups per category

  • PSIRA / industry‑regulated minimums

• Plug real HTTP APIs into fetch_market_prices.py once you have a host that allows outbound HTTP.

7. Safety Notes

• This server does no remote network calls by default.

• All calculations are purely local and deterministic.

• Perfect for running inside constrained MCP hosts (FastMCP Cloud, Cursor, Claude Desktop, etc.).