Acikpoz
FreeNot checkedMCP server for parsing, diffing, and validating Turkish public construction unit price catalogs (ÇŞB birim fiyat) from PDFs, enabling AI agents to compute with
About
MCP server for parsing, diffing, and validating Turkish public construction unit price catalogs (ÇŞB birim fiyat) from PDFs, enabling AI agents to compute with structured price data.
README
Turkish public construction unit prices, turned from a PDF into data you can compute with.
Every public construction job in Turkey is priced against a government catalog: the ÇŞB (Çevre, Şehircilik ve İklim Değişikliği Bakanlığı) birim fiyat books — thousands of unit prices (a poz: a code, a description, a unit, a price) that estimators, contractors and auditors all read. They ship as long PDFs. acikpoz turns those pages back into structured records, deterministically, so a cost estimate or a tender preparation can be computed instead of copied by hand.
It is disciplined geometry, not a language model: it groups the words on a page into visual rows and reads the price column's position from the page header rather than guessing a fixed spot. That one decision is what makes it trustworthy — some sections (Sıhhi Tesisat, say) print two numbers per row, the real Birim Fiyat and a separate Montaj Bedeli, and a naive parser silently reads the wrong one. acikpoz reads the header, so it reads the right column.
Paired with ihalent (which structures tender results), acikpoz covers the other half of Turkey's public construction economy: the prices the results are measured against.
The one rule it never breaks
A price is only ever a number the catalog actually printed in the price column. It never coerces, never borrows a neighbour's figure, never guesses. Two consequences, both on purpose:
- A group-header poz — a category title like
EVİYELER:whose sub-items carry the real prices — has no price of its own. acikpoz leaves itsfiyatasNoneand flagsis_group_header. It does not invent a zero. - A poz the catalog left without a printed price is a gap, surfaced and counted, not hidden. Every result reports its coverage: how many pozes were priced, how many were headers, how many were genuine gaps.
Half the value of a cost tool is refusing to make up the numbers the source did not print. That is the same honesty discipline as andon and ihalent.
Install
pip install acikpoz # add [mcp] for the MCP server: pip install "acikpoz[mcp]"
Quick start
Point it at an official catalog PDF you have (acikpoz ships the parser, not the data):
acikpoz parse bf2026.pdf --pages 8-20
acikpoz parse bf2026.pdf --json > pozes.jsonl # one poz per line, for pipelines
acikpoz parse bf2026.pdf --csv pozes.csv # Excel-ready (utf-8-sig, Turkish text)
acikpoz parse bf2026.pdf --group 25 # only Sıhhi Tesisat pozes
acikpoz parse bf2026.pdf --priced-only # drop headers and gaps
The table view — this is a real run against the published 2026 catalog, not a mock-up:
Two things in that picture are the whole point:
- Three rows carry
-in the price column. The catalog printed no price for them, so acikpoz prints none either — they are counted as gaps, not filled in from a neighbour. validatethen flags what the parse is not sure about: on this page five units (+2000,azami,Yapı,-30°C,2,5) are fragments of description text that landed in the unit column. The extraction is imperfect on some layouts, and the tool reports that itself rather than handing you a clean-looking table with wrong units in it.
Reproduce it — the page is chosen, nothing else is:
acikpoz parse bf2026.pdf --pages 400
acikpoz validate bf2026.pdf --pages 400
The catalog is the ministry's own file, published here. The image is regenerated by scripts/make_demo_svg.py, which downloads that PDF and runs the same code the CLI runs.
The grade (excellent/good/fair/poor) is a glanceable confidence signal, the
way camelot exposes accuracy: below good, review the pages before trusting the
output. --json includes price_parse_rate and grade per parse.
Or from Python:
from acikpoz import parse_catalog
result = parse_catalog("bf2026.pdf", pages=range(8, 20))
for p in result.pozes:
if p.is_priced:
print(p.poz_no, p.birim, p.fiyat)
print(result.to_dict()["counts"]) # priced / group_headers / price_gaps
How it works
- Rows. Words are grouped into visual rows by vertical position (a few points of tolerance), then sorted left-to-right.
- Price column, from the header. The
Fiyatheader word on the right (x > 400) gives the price column's x. A stray "fiyat" in a left-column description can't be mistaken for it. - Cells. For each poz row: the leftmost cell is the poz code; the price is the number-shaped token nearest the price-column x; the unit sits just left of it; the rest is the description. Indented continuation lines extend the running description (and can carry a price that spilled over).
- Group headers. A price-less poz whose description ends in
:is a category title — flagged, not treated as a gap.
Compare two catalog years
Catalogs are reissued regularly; the question estimators and auditors track by hand is how
did this year's rates move from last year's? acikpoz diff answers it — it joins two years
by poz code and classifies each change:
acikpoz diff bf2025.pdf bf2026.pdf --pages 8-400
acikpoz diff bf2025.pdf bf2026.pdf --tolerance 1 # hide sub-1-TL rounding noise
acikpoz diff bf2025.pdf bf2026.pdf --json
It reports price moves (with Δ and %Δ), added and removed pozes, unit changes, and pozes that gained or lost a printed price — plus the mean price %-change for the year. As far as the research found, no other open tool does year-over-year diffing for ÇŞB catalogs.
Validate a parse
Before a parsed catalog feeds a cost estimate, it helps to know it is clean. acikpoz validate runs deterministic quality rules over the pozes — no ML, no fixing, only surfacing:
acikpoz validate bf2026.pdf --pages 8-400
acikpoz validate bf2026.pdf --json
It flags duplicate poz codes, malformed codes, non-positive prices (errors), and priced
pozes with no unit or a unit outside the known set (warnings). It exits non-zero on any
error, so it can gate a pipeline (acikpoz validate … && build-estimate). This is also how
acikpoz stays honest about its own limits: in sections that print the unit once on a group
header and let the rows inherit it (Sıhhi Tesisat), per-row unit detection is weak, and
validate says so rather than hiding it. Price, poz code and description stay reliable.
Using acikpoz with AI agents
An MCP server (pip install 'acikpoz[mcp]', then acikpoz-mcp) exposes three tools:
parse_catalog (a PDF → structured pozes with honest coverage), diff (two catalog years
→ classified changes), and validate (a PDF → quality findings). The agent gets structured
data back, not prose it has to parse. Pair it with ihalent and an agent can reason across
both a tender's result and the unit prices it was measured against.
// e.g. Claude Desktop / Claude Code mcp config
{ "mcpServers": { "acikpoz": { "command": "acikpoz-mcp" } } }
Scope, honestly
- It reads the standard catalog layout. The header-driven column detection handles the common single- and two-price-column pages well; an unusual layout may leave more gaps — which it reports rather than papering over. If a section parses badly, that's a bug worth a sample.
- It is a parser, not a price database. It does not bundle or redistribute the catalog. You bring the official PDF; acikpoz turns your copy into data.
- Prices are nominal, as printed. No inflation adjustment is baked in — that's an analysis choice the caller makes knowing the year.
Data, and why the PDFs aren't here
The ÇŞB catalogs are official public documents, but this repository does not redistribute
them: it ships the parser and nothing else, and .gitignore keeps *.pdf out. Point acikpoz
at the catalog you obtained from the official source. This is the same line ihalent draws —
own the tool, not the data.
How this project is built
I'm an industrial engineer working in construction; I read these catalogs. I designed the parsing approach — geometry over machine learning, honest gaps over invented numbers — and I review every line; I use AI agents heavily for implementation speed, and the commit trailers say so. The contract is the tests: they encode the exact word geometry a real page emits, including the two-column Sıhhi Tesisat trap and the group-header rule, so green tests mean the parser handles the real thing.
Related
- ihalent — the other half of the Turkish public-procurement picture.
acikpozreads the unit-price catalogs that say what work should cost;ihalentreads the tender result notices that say what it was awarded for, and at what discount. Same discipline: every figure traceable to its source, nothing invented.
More tools by Eren Gülmez.
License
MIT — see LICENSE.
Installing Acikpoz
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/gulmezeren2-byte/acikpozFAQ
Is Acikpoz MCP free?
Yes, Acikpoz MCP is free — one-click install via Unyly at no cost.
Does Acikpoz need an API key?
No, Acikpoz runs without API keys or environment variables.
Is Acikpoz hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Acikpoz in Claude Desktop, Claude Code or Cursor?
Open Acikpoz on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
by modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
by xuzexin-hzMCP-Agent
A simple, composable framework to build agents using Model Context Protocol by [LastMile AI](https://www.lastmileai.dev)
by lastmile-aiSpring AI MCP Client
Provides auto-configuration for MCP client functionality in Spring Boot applications.
mcp.natoma.ai
A Hosted MCP Platform to discover, install, manage and deploy MCP servers by [Natoma Labs](https://www.natoma.ai)
MCPHub
Website to list high quality MCP servers and reviews by real users. Also provide online chatbot for popular LLM models with MCP server support.
MCP Servers Rating and User Reviews
Website to rate MCP servers, write authentic user reviews, and [search engine for agent & mcp](http://www.deepnlp.org/search/agent)
mkinf
An Open Source registry of hosted MCP Servers to accelerate AI agent workflows.
Compare Acikpoz with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All ai MCPs
