Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Turkish public-tender (EKAP) award intelligence: firm histories, discounts, competition, red flags
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"ihalent": {
"command": "uvx",
"args": [
"ihalent"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add ihalent -- uvx ihalent프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"ihalent": {
"command": "uvx",
"args": [
"ihalent"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"ihalent": {
"type": "stdio",
"command": "uvx",
"args": [
"ihalent"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 10일 점검
레지스트리 이름이 GitHub 계정 gulmezeren2-byte 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.0)은 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Beefi
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
US public company data from SEC EDGAR: financials, insider trades, 13F holdings, filings and macro.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Turkish public-tender award intelligence: who won, for how much, at what discount, against how many bidders.
Built on top of [saidsurucu/ihale-mcp](https://github.com/saidsurucu/ihale-mcp) — ihale-mcp reaches EKAP; ihalent structures and analyzes what it returns.
Every public tender in Turkey ends with a *Sonuç İlanı* — a result notice that states the estimate, the contract price, the winner, and how many firms bid. The notices are public. They are also one at a time, unstructured, and impossible to reason across: you cannot ask EKAP "what has this company won in the last two years" or "how far below estimate does this authority actually award." ihalent turns those notices into structured records and answers exactly those questions — firm histories, discount (kırım) distributions, and competition metrics — with every number traceable back to the notice it came from.
That is real output over nine real construction awards from the December-2025 / January-2026 window (in examples/). The -2.96% at the bottom of the range is not a bug: Istanbul University awarded a 615-million-lira campus job at 2.96% above its own estimate, through an emergency "pazarlık" procedure — a contract signed over the public estimate, which is precisely the kind of thing that should be easy to see and currently is not.
I'm an industrial engineer and I work in construction. When our firm weighs a public tender, the questions that decide the bid are all about other people's history: how far below estimate does this authority award, how many firms usually show up, what has a given competitor been winning and at what price. All of that is public — it is sitting in tens of thousands of result notices on EKAP — and none of it is queryable. So everyone rebuilds a private, partial version of it by hand, in spreadsheets, badly.
There is already an excellent tool for *reaching* this data: saidsurucu/ihale-mcp solved authenticated EKAP access and hands you the notices. ihalent is the layer above it — the one that turns a pile of notices into an answer. It does not re-scrape EKAP; it structures what you have collected and does the analytics that don't exist yet.
A firm's history — every award across the dataset, folded across spelling variants:
$ ihalent firm examples/sample-awards.jsonl "ÖZDEN YEL"
ÖZDEN YEL wins: 1 joint ventures: 1 total contract value: 19.709.997,40 TL Discount (kırım) — ÖZDEN YEL ┌────────┬────────┬────────┬────────┐ │ mean │ median │ min │ max │ ├────────┼────────┼────────┼────────┤ │ 33.87% │ 33.87% │ 33.87% │ 33.87% │ └────────┴────────┴────────┴────────┘ based on all 1 awards. top awarding authorities: 1x DSİ 14. Bölge Müdürlüğü
Where the discounts are — grouped and sorted, highest first:
$ ihalent discounts examples/sample-awards.jsonl --by authority
Mean discount by authority ┌──────────────────────────────────┬────────┬────────┬────────┐ │ authority │ mean │ median │ awards │ ├──────────────────────────────────┼────────┼────────┼────────┤ │ DSİ 14. Bölge Müdürlüğü │ 33.87% │ 33.87% │ 1/1 │ │ Ziraat Bankası Genel Müdürlüğü │ 31.41% │ 31.41% │ 1/1 │ │ İstanbul YİKOB │ 26.98% │ 26.98% │ 1/1 │ │ İSKİ Genel Müdürlüğü │ 26.66% │ 26.66% │ 1/1 │ │ İTÜ Rektörlüğü │ 22.68% │ 22.68% │ 1/1 │ │ Esenler Belediyesi │ 21.99% │ 21.99% │ 1/1 │ │ Ağrı İl Özel İdaresi │ 19.99% │ 19.99% │ 1/1 │ │ Kağıthane Belediyesi │ 17.41% │ 17.41% │ 1/1 │ │ İstanbul Üniversitesi-Cerrahpaşa │ -2.96% │ -2.96% │ 1/1 │ └──────────────────────────────────┴────────┴────────┴────────┘ awards column: used / considered (excluded lack an estimate).
Competition — how many valid bids show up, and how often exactly one does (a single-bid award is a flag procurement watchdogs care about). It's in the overview above.
A number is never shown without the ground it stands on. A mean discount always comes with "over how many awards, and how many were dropped for a missing estimate." A firm's total contract value says so when some of its wins had no published price, so you read it as a floor, not the full figure. A discount is None, never 0, when the estimate wasn't published — ihalent does not invent the numbers the government didn't print. Half the value of a tool like this is refusing to guess.
pip install ihalent # add [mcp] for the MCP server: pip install "ihalent[mcp]"
Or from source: pip install git+https://github.com/gulmezeren2-byte/ihalent.
ihalent reads a JSONL file of awards. You produce it by collecting result notices — the easy path is ihale-mcp — and letting ihalent structure them:
# 1. collect: with ihale-mcp connected to your agent, save what its
ihalent ingest bundle.json -o awards.jsonl
ihalent overview awards.jsonl ihalent firm awards.jsonl "ACME İNŞAAT" ihalent discounts awards.jsonl --by province --min 5
Every command takes --json for pipelines and agents. Or skip collection and try the bundled example directly:
git clone https://github.com/gulmezeren2-byte/ihalent && cd ihalent
python examples/build_sample.py # parses the real notices in examples/notices/ ihalent overview examples/sample-awards.jsonl
| command | what it does |
|---|---|
ihalent overview AWARDS | value, discount, competition and the data gaps of a dataset |
ihalent firm AWARDS "NAME" | one company's wins, total value, discount, and where it wins |
ihalent discounts AWARDS --by X | mean/median discount grouped by authority, province or tender_type |
ihalent single-bid AWARDS | awards with a single valid bid — no real competition (a watchdog flag) |
ihalent concentration AWARDS [--authority X] | winner concentration (HHI) — do the same few firms win everything? |
ihalent flags AWARDS | per-award red flags: single bid, near-estimate price, no estimate, high drop-off |
ihalent parse NOTICE.md | one result notice → structured JSON |
ihalent ingest BUNDLE.json | collected ihale-mcp/EKAP output → awards JSONL |
The result notice is unstructured text; the interesting questions are aggregate. That is an awkward fit for an agent working notice-by-notice, and a natural fit for a tool: --json output with stable fields, an exit code that means something, and a firm-name match that folds spelling variants so an agent doesn't have to.
There is a native MCP server (pip install 'ihalent[mcp]') that exposes the analytics as tools — overview, firm, discounts, concentration, flags, parse_notice, ingest_bundle — over a dataset you point it at:
IHALENT_AWARDS=awards.jsonl ihalent-mcp
No local Python? The Dockerfile builds the same server: docker build -t ihalent . && docker run --rm -i -e IHALENT_AWARDS=/data/awards.jsonl -v "$PWD:/data:ro" ihalent.
Pair it with ihale-mcp and an agent can collect notices and reason across them in one session: ihale-mcp fetches, ihalent structures and aggregates. The Python API (ihalent.ingest_bundle, ihalent.analytics.firm_profile) is three calls deep if you'd rather script it.
firm reports how many distinct spellings a query matched, and warns you if that is more than one.It is not a replacement for ihale-mcp — it sits on top of it. It is not a live dashboard or a paid tender-alert service; it is a library and a CLI you point at data you control. And it does not redistribute a dataset: it ships the handful of real notices in examples/ and the code to structure your own.
Public-tender results are public information, published by the state for public scrutiny. ihalent structures what EKAP already discloses. Company names that appear are legal entities in their public commercial capacity, not private individuals.
I designed the model and the analytics and I review every line; I use AI agents (Claude Code) heavily for implementation speed, and the commit trailers say so. The contract is the tests — 80 of them, built on the exact JSON shapes EKAP and ihale-mcp emit, including a result notice with a negative discount and a cancelled tender. They don't care who typed them.
ihalent reads the tender result notices that say who won and at what discount; acikpoz reads the unit-price (birim fiyat) catalogs that say what the work *should* have cost. Same discipline: every figure traceable to its source, nothing invented.More tools by Eren Gülmez.
MIT — Mehmet Eren Gülmez