プロトタイプ · プレビュー版:公式レジストリのすべてのサーバーを掲載し、30分ごとに同期しています。レビューとアカウント機能は今後のステップで始まります。
PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Celmis

作者:Celmis-labsバージョン 0.1.30i★ –iパソコンで動く
レジストリ名io.github.constantinemakoid/celmis

インストール

概要

作者による説明(英語の原文)

Self-hosted code intelligence: cross-repo Q&A, dependency audits and PR review, over MCP

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: パソコンで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: その他

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

  • 基本チェック:1項目中0項目に合格
  • あなたのパソコンで、あなたのユーザーと同じ権限(ファイル、ネットワーク、アプリ)で動きます。
  • レジストリには、入力が必要なキーは載っていません。

必要なもの

  • DockerDockerのインストール

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます

{
  "mcpServers": {
    "celmis": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/celmis-labs/celmis-api:v0.1.30"
      ]
    }
  }
}

ターミナルでこれを実行します

claude mcp add celmis -- docker run -i --rm ghcr.io/celmis-labs/celmis-api:v0.1.30

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

{
  "mcpServers": {
    "celmis": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/celmis-labs/celmis-api:v0.1.30"
      ]
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

{
  "servers": {
    "celmis": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/celmis-labs/celmis-api:v0.1.30"
      ]
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック

  • ! 注意

    作者とリポジトリが一致

    公開者(constantinemakoid)がリポジトリの所有者(Celmis-labs)ではありません。別の人が登録した可能性があります

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • – 対象外

    エンドポイントが応答する

    これはパソコンで動くため、インターネット上のエンドポイントはありません

  • – 対象外

    OAuthでサインイン

    パソコンで動き、代わりにローカルの設定を使います

  • … 未チェック

    ツールの説明に隠れた指示がない

    パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです

その他のほかのサーバーとの比較i

  • このカテゴリのほかの32537件のうち0%よりスターが多い
  • このカテゴリのほかの32537件のうち43%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの32537件のうち32%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Celmisは安全ですか?

当てはまる基本チェック1項目のうち0項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.1.30)がレジストリに届いたのは2 か月前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにDockerも必要です。

代わりに使えるものは?

同じカテゴリには:Spec Driven Development, Remote Desktop Commander, TF Rooms

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

クラウドで動く★ 211昨日更新
インストール

TF Rooms

作者:tfrooms.com

Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.

クラウドで動く今日更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

Celmis

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:

  • understand code nobody documented: questions across repositories answered with 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;
  • review pull requests with what the change touches beyond its own repository;
  • secure the dependencies: CVE audit, a CycloneDX SBOM and an evidence pack a third party can verify;
  • fix what an alert or a finding points at: an embedded Claude Code session on *your* subscription edits the code and the runner opens a pull request (220 seconds on one measured finding). A person reviews and merges; Celmis never merges or deploys.

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.

What it does

Ask the codeQuestions across several repositories, answered with file:line citations on both sides of a call. Ask the code
Codebase and MCP51 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 reviewAgents 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
EvidenceDependency audit, CycloneDX SBOM and an evidence pack whose manifest a third party recomputes. SBOM and evidence
Fix from hereAn 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 defendRepositories 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

Install

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.

What's new in v3

  • Review that earns its comments. Findings below your comment level never reach the pull request; a review with nothing to say approves. Comments are the problem, the reason and the fix, in the repository's language (3.1).
  • A reviewer you can talk to. @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).
  • Knowledge packs. Versioned skills, API examples and checklists per workspace, readable in the app and by coding assistants through brief and skills; celmis-pack publishes them (3.0).
  • Access closed by default. A repository nobody has a rule for is invisible; MCP tokens belong to a person; every call is audited (2.3.7). Stricter secret hiding in 3.0.2.
  • Sharing between workspaces. For research, for a fixed time, with hidden paths and a ceiling on readers (3.1).
  • A developer MCP profile and a Claude Code plugin sized for an editor (2.3.7).

Every release is in the changelog.

Logs, and where the line falls

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.

What that buys you that a diff-only tool cannot

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.


Nine things people do with it

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 worksAsk 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 answerEvery 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 repositoryLoad 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 SBOMOne 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 reviewingAgents 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 themWrite 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 deskIt 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 codebasePoint 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.

Three numbers

197 secondsfrom git clone to six healthy services, measured on a clean server
$0.118per pull request reviewed, on the model this ships with
17th of 50on 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.

Table of contents

  • What it does
  • What's new in v3
  • What that buys you that a diff-only tool cannot
  • Nine things people do with it
  • Three numbers
  • Quick start
  • First user and admin
  • Connect a repository
  • Ask the code
  • Pull-request review
  • Dependencies, SBOM and the evidence pack
  • Fix from here
  • Alerts, and fixing from a phone
  • Ask for work across repositories
  • Who can see what
  • Languages and formats
  • Deterministic checks — no model, no false positives
  • Connect Claude Code and other MCP clients
  • Results
  • Audit of the false positives
  • Test repositories
  • Configuration
  • Operations
  • Local development
  • CLI reference
  • Architecture
  • Troubleshooting
  • Project layout
  • Provenance and rights

Quick start

What you need
Docker24+ with Compose v2Docker Desktop on macOS/Windows, the native engine on Linux
A model API keyone ofGoogle Gemini, Anthropic, OpenAI, OpenRouter, Groq or Mistral. A free Gemini key is enough to evaluate: https://aistudio.google.com/app/apikey
RAM~4 GB freeMeasured on a real indexing run: 1.1 GB peak across all five containers, 565 MB at rest

Postgres and Qdrant are **bundled

冒頭だけを表示しています。続きはリポジトリで読めます

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