Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Consult other LLMs as tools — ask them, compare their answers, synthesize a conclusion.
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.
COUNCIL_MODELS, COUNCIL_CONFIG필요한 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": {
"model-council": {
"command": "uvx",
"args": [
"model-council-mcp"
],
"env": {
"COUNCIL_MODELS": "your-value",
"COUNCIL_CONFIG": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add model-council --env COUNCIL_MODELS=your-value --env COUNCIL_CONFIG=your-value -- uvx model-council-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"model-council": {
"command": "uvx",
"args": [
"model-council-mcp"
],
"env": {
"COUNCIL_MODELS": "your-value",
"COUNCIL_CONFIG": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"model-council": {
"type": "stdio",
"command": "uvx",
"args": [
"model-council-mcp"
],
"env": {
"COUNCIL_MODELS": "your-value",
"COUNCIL_CONFIG": "your-value"
}
}
}
}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.
COUNCIL_MODELS envCOUNCIL_CONFIG env이 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 7일 점검
레지스트리 이름이 GitHub 계정 Totti0135 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(0.14.0)은 2개월 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, MCP Server Autocad Lisp Helper
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ 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.
High-precision static analysis and debug server for AutoCAD AutoLISP (.lsp) files.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
English | 简体中文
An MCP server that seats other LLMs at your table. Your assistant asks them, reads their answers as tool results, relays those answers back and forth for critique, and gives you one merged conclusion — inside a single normal conversation, with no copy-paste.
Your assistant chairs the council. Any number of members, from any mix of OpenAI-compatible and Anthropic-compatible endpoints — a hosted API, a self-run gateway, a local server, or several of each.
| Tool | What it does |
|---|---|
ask(model, prompt, materials?) | Ask one member by id |
ask_all(prompt, models?, rounds?, guests?, materials?, steelman?) | Ask everyone (or a named subset) the same prompt in parallel, answers side by side. rounds=2 turns it into a discussion; steelman seats a standing objection that argues back every round; guests seats answers you already have; materials hands them a file to read |
revise(prompt, answers, round?, materials?) | Run one more round yourself: show the members everything said last round — including answers only you can produce — and get them back revised |
revision_prompt(prompt, answers, seat, materials?) | The prompt to hand your own seat for the next round, word-for-word what the members got. No network calls |
list_council() | The roster: ids, endpoints, weights, what each member can be shown, the route each takes out, call budget, and whether it is ready. No network calls |
probe_models(model?) | Ask a provider's /models route what ids it really exposes |
Members are stateless and cannot see your conversation, so the chair passes everything they need in each call. That is exactly what makes cross-review work: it puts one member's answer inside another's prompt.
A question is usually about something — a spec, a log, a diff, a screenshot. The obvious way to include it is to paste it into prompt, and that is the expensive one, in the place nobody watches: prompt is an argument the chair *writes*, so a long document costs a full copy of itself in generated tokens on every call, and what reaches the members is whatever the chair managed to reproduce. For forty pages that is not reliably the document. A council reviewing a paraphrase is not reviewing the thing, and nothing in the transcript would say so.
materials names it instead:
ask_all(
prompt="Where would this break under load?", materials=[ {"label": "The design", "path": "/abs/path/design.md"}, {"label": "Latency graph", "path": "/abs/path/p99.png"}, {"label": "My summary", "text": "…something with no file behind it…"}, ], rounds=2, )
The server reads each one and puts it ahead of the question, in the same place for every member and every round. The position is not presentation:
cache_control breakpoint at that boundary; endpoints that cache by prefix on their own get the shape they need either way. Set "cache": false on a member whose gateway rejects the field.ask_all carries the material into round 2 and 3 by itself.Images are the case that matters most. Without them the chair has to describe the screenshot in prose — and then every member reads the *same* description, so anything the chair misread is misread by the whole council at once, and cross-review cannot recover it. It is the one input where passing it badly quietly removes the independence the council is for. Png, jpeg, gif and webp go to every member whose model can see; a member that cannot should be configured "vision": false, and it then sits out the calls that carry an image rather than answering about text alone as though it had seen the picture. The transcript names who sat out.
How to tell which members those are: a member that cannot see rarely says so. One Anthropic-compatible gateway tested while building this accepted the image blocks, discarded them, and the model then named a colour — not "I was sent no image", which the prompt had explicitly asked for in that case. Text material through the same endpoint arrived intact, so nothing about the call looked wrong. Show a member one unambiguous picture and ask what is in it; a confidently wrong answer is the symptom, and "vision": false is the fix.
Two limits worth knowing. A material that cannot be read stops the call — a council asked about a document it never received will answer anyway, fluently, and read exactly like one that had. And revision_prompt *names* your files rather than pasting them back, at the position the members were given them, so open them for your own seat before you hand it the rest.
Whether this server will read a path at all depends on how it was started; over HTTP it will not, unless its operator named a directory. list_council says which, in a line above the table.
ask_all(prompt, rounds=2) runs that cross-review for you. Round 1 is the usual parallel ask. Round 2 goes back to each member carrying the question plus every answer from round 1 — its own and the others', verbatim — and asks it to revise: take what is right, correct what is not, and say where it still disagrees and why. The transcript comes back round by round, so you can see who moved and who held their ground.
Carrying the previous round back is the whole mechanism. Members remember nothing between calls, so without it a second round is just the same question asked twice. Up to 3 rounds; each one costs another call per member and a longer prompt than the last, so 1 is right for a survey of opinion and 2 for a question where the disagreement is the interesting part.
`rounds` is chosen before anything has been asked, which is the one thing wrong with it: you commit to a second round without having read the first, and a council that turns out to agree costs exactly what one still arguing would. Ask with rounds=1 when you would rather look first, then buy the next round with revise — it runs exactly one more, as many times as you judge it worth, and has no ceiling of its own. Reading before you buy is usually the cheaper side: another round is a full call per member, while revise costs you only the answers written back into it. The 3 on ask_all is a ceiling on what one call will spend, not on what the discussion can have, and the transcript says so when you reach it.
Members can also carry different weights, for the common case where the council is not a council of equals.
A council mostly agrees, and its agreement is the least informative thing it produces. Everything above works *against* convergence — the members are anonymous to each other, they are never told the weights, and the closing instruction tells them not to cave — but none of it creates any pressure to diverge. The strongest objection to a plan is not volunteered by members who think the plan is fine.
steelman seats one:
ask_all(prompt, rounds=3, steelman={})
One member writes the strongest case against whatever the table has converged on, each round, and it goes back to everyone as an ordinary anonymous answer. In the next round they have to deal with it.
No member is told to argue a side it does not hold. That is the line, and it is what separates this from a debate mode. What the members say is still what they think; the assignment lives in one extra call they are never told about. Handed a seat marked "arguing against", a model discounts the argument instead of answering it — so the provenance goes to you, in a note at the end of the transcript, and the argument goes to them.
It speaks every round, not once. This is the part that looks like a detail and is not. An objection that cannot reply to its own rebuttal is *quoted* rather than represented: it cannot correct a misreading of itself, so by the third round the table is arguing with its paraphrase and calling that an answer. tenure buys fewer rounds than the default, and when the seat is retired early the transcript says it was retired by configuration — because an unexplained silence reads exactly like a position abandoned.
The mirror of that is worth as much: the last thing the objection says is the last thing in the transcript, so nobody has been asked to take it on, and the transcript says that too. An objection nobody answered is not a point that stood — it is a point that was never examined. With rounds=2 that is true of everything it said, which is why the note names the setting that fixes it rather than leaving you to notice after paying.
Read what it produces as the strongest objection this council can make to order, never as evidence that anyone holds it. A point of its that survives being answered is worth something; the same point in the round it appeared is worth nothing yet.
By default the first member being asked writes it, and also answers as itself — the two calls are unrelated as far as it knows. Name another with steelman={"model": "glm"}.
Your assistant is not only the chair — it can answer too, and in Claude Code or Codex it can spawn a subagent to answer as well. Those answers used to sit *beside* the council's, compared by hand at the end. guests puts them *in* it:
ask_all(
prompt="What are the traps in this plan?", guests=[{"label": "Subagent", "text": " "}], rounds=2, )
Round 1 prints it beside the members. From round 2 every member is handed the text verbatim and asked to argue with it:
--- ANSWER C (does not revise between rounds) ---
the migration has no rollback path
That is the whole difference. Without it the models never learn your subagent had an opinion, and you are left doing the comparison yourself — which is the work the rounds mechanism already does better, because it lets the models answer each other rather than answering into a void.
Notes worth having:
A guest speaks once. To let a voice you produce yourself *keep up* with the members — answer, read the others, revise, round after round, exactly as they do — you have to drive the rounds, because this server cannot spawn your subagent. revise runs one round on demand:
ask_all(prompt) → members answer round 1
...you spawn your subagent on the same prompt → its round-1 answer
revise(prompt, round=1, answers=[ {"model": "glm", "text": " "}, {"model": "sol", "text": " "}, {"label": "Subagent", "text": " "}, ]) → members come back revised ...you re-run your subagent on the same material
revise(prompt, round=
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요