Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Self-hosted code intelligence: cross-repo Q&A, dependency audits and PR review, over MCP
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": {
"celmis": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/celmis-labs/celmis-api:v0.1.30"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add celmis -- docker run -i --rm ghcr.io/celmis-labs/celmis-api:v0.1.30프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"celmis": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/celmis-labs/celmis-api:v0.1.30"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"celmis": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/celmis-labs/celmis-api:v0.1.30"
]
}
}
}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 6일 점검
게시자(constantinemakoid)가 저장소 소유자(Celmis-labs)가 아니에요. 다른 사람이 등록했을 수 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 0개를 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(0.1.30)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Docker도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Apify MCP Server
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.
Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Understand, review, secure and fix your code, in one self-hosted place. One machine. Your model, your network. The code never leaves the company.
Website · Documentation · Quick start · What's new · Results
Celmis puts everything an engineering team needs to work with its code in one place. It indexes all of your repositories once, into a symbol graph built without a model, and every tool reads that same index:
file:line citations, in the app or from a coding agent (Claude Code, Cursor, Codex) over MCP, plus the team's own skills and checklists for the task at hand;It is built for the team that ships the code and answers for it in production. Instead of a separate tool for each of those jobs, each with its own access rules and its own copy of your code, one installation holds them all. The aim is a small team that can run several products and the integrations between them.
What "beyond its own repository" means today. Before a merge, the review checks the other repositories for values the change removes that they still hardcode, for deploy files that point at the changed repository, and for code that calls a changed function by the same name, quoting both sides. These are checks, not a call graph between repositories; that graph is not built yet.
| Ask the code | Questions across several repositories, answered with file:line citations on both sides of a call. Ask the code |
| Codebase and MCP | 51 tools over MCP, a compact /mcp/dev profile for editors, a Claude Code plugin, and versioned knowledge packs of the skills your team already explains out loud. MCP · Packs |
| Pull-request review | Agents read the diff and, where the graph exists, who else calls what changed, across repositories. Talk to it with @celmis, teach it with remember, and it stays quiet when there is nothing to say. Review |
| Evidence | Dependency audit, CycloneDX SBOM and an evidence pack whose manifest a third party recomputes. SBOM and evidence |
| Fix from here | An alert or a dependency finding becomes an embedded session, then a branch, then a pull request. A human reviews and merges; Celmis never merges. Fix from here · Alerts |
| Access you can defend | Repositories are closed by default, MCP tokens are issued per person, every call is audited, secrets are withheld at the source, and a repository can be shared with another workspace for a fixed time. Who can see what · Sharing |
git clone https://github.com/Celmis-labs/Celmis.git celmis && cd celmis
./scripts/init-env.sh # writes .env and fills every secret docker compose --env-file .env up -d
Then open http://localhost and paste one model provider key under Settings → LLM Setup.
197 seconds from clone to six healthy services on a clean server. Postgres and Qdrant are bundled; about 4 GB of RAM. Details in Quick start. An installation without a licence admits up to five people; see Licensing.
@celmis commands and questions in the thread, remember rules, learning from what the team dismisses, incremental review of each push, Jira acceptance criteria checked in the summary (2.3).brief and skills; celmis-pack publishes them (3.0).Every release is in the changelog.
Celmis does not watch your services; Grafana or whatever you already run does that. The application ingests no logs of its own and starts from the alert. The repository ships an optional observability overlay (Prometheus, Loki, Promtail, Grafana) that does collect them, platform-wide rather than Celmis-only:
docker compose -f docker-compose.yml -f docker-compose.observability.yml up -d
Every port binds to 127.0.0.1 and is reached over an SSH tunnel, because Loki has no authentication. GRAFANA_ADMIN_PASSWORD is required.
Ask a question that spans two repositories, and the answer quotes both, as in the screenshot at the top of this page. That is not a search result. The gateway and the payments service are separate repositories with no shared code, and the answer traces the call chain between them — then notices, unprompted, that the Kafka topic name is hardcoded in both and that changing one silently breaks the other.
A reviewer that reads only the diff structurally cannot say that. It never had the other repository open.
| You are a PM, a delivery lead or the client and want to know what state a group of projects is in, or how something actually works | Ask it. From any device, anywhere, without booking time from an engineer and without a meeting whose only output is a paragraph → Ask the code |
| A new engineer has a question a senior would have to answer | Every one of those pulls someone experienced out of flow, at the moment they are already covering. The codebase answers instead, with file:line citations → Ask the code |
| Two teams share an integration and neither can read the other's repository | Load it, grant the right to ask, and deny the paths that must stay private. They get answers; the credentials are refused at the source → Who can see what |
| A customer or an auditor asks for your SBOM | One button, CycloneDX, plus an evidence pack whose manifest they recompute themselves — against a hash you publish where the pack is not → Dependencies, SBOM and the evidence pack |
| A vulnerability lands in a dependency | *Fix from here* hands an embedded session the repository, the package and the finding. It edits, the runner pushes a branch and opens a PR → Fix from here |
| A pull request needs reviewing | Agents read the diff — and, where the graph is built, who else calls what is being changed, including from another repository → Pull-request review |
| Forty services need the same thing done to them | Write the sentence. Celmis shows which repositories it resolves to and waits for a second press, rather than finding them among forty and pressing a button forty times → Ask for work across repositories |
| An alert fires at 02:00 and you are not at a desk | It lands in Celmis and goes out to the workspace's chat channel, and *Fix from here* opens a session already holding the alert. The runner opens the pull request → Alerts, and fixing from a phone |
| Your own agent or editor needs to understand the codebase | Point it at /mcp/. Fifty-one tools over the same index, thirty-five of them read-only, under the same access rules — no second copy of your code anywhere → Connect Claude Code and other MCP clients |
The first three are the ones a code-review tool does not do at all, and they are the reason this is a platform rather than a reviewer: index once, then read that index from whichever side of the work you are standing on.
| 197 seconds | from git clone to six healthy services, measured on a clean server |
| $0.118 | per pull request reviewed, on the model this ships with |
| 17th of 50 | on the Martian Code Review Bench offline set, under all three judges |
That last one is deliberately unflattering, and it stays. It measures one of the surfaces below — pull-request review on isolated single-repository PRs — and that set has no sibling service for a symbol to have consumers in, so the thing this product is built around is not in the number at all. The table, the audit of every finding it scored false, and the command that reproduces both are in Results.
| Docker | 24+ with Compose v2 | Docker Desktop on macOS/Windows, the native engine on Linux |
| A model API key | one of | Google Gemini, Anthropic, OpenAI, OpenRouter, Groq or Mistral. A free Gemini key is enough to evaluate: https://aistudio.google.com/app/apikey |
| RAM | ~4 GB free | Measured on a real indexing run: 1.1 GB peak across all five containers, 565 MB at rest |
Postgres and Qdrant are **bundled
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요