Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Rust MCP gateway with Code Mode, authentication, setup, logs, CLI, HTTP API, and operator web UI.
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。
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。
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。
LABBY_VERSION, LABBY_REPO, LABBY_LOG必要なもの
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": {
"labby": {
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add labby --env LABBY_VERSION=your-value --env LABBY_REPO=your-value --env LABBY_LOG=your-value -- npx -y @dinglebear/labby mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"labby": {
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}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。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"labby": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}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。
LABBY_VERSION envLABBY_REPO envLABBY_LOG env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。
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。
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6日にチェック
レジストリ名はドメイン dinglebear.ai で確認済みです(レジストリがドメインの所有を確認しています)
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
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
パソコンで動き、代わりにローカルの設定を使います
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
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。
当てはまる基本チェック1項目のうち1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。
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。
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)。
GitHubリポジトリの最終更新は–、最新バージョン(2.6.2)がレジストリに届いたのは27 日前です。
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Node.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
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
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.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
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。
Rust MCP gateway with Code Mode, authentication, setup, logs, CLI, HTTP API, and operator web UI.
Canonical remote: git@github.com:dinglebear-ai/labby.git.
The root README is the public entrypoint. The topic docs in docs/ own the detailed contracts; when this file and a topic doc disagree, fix the topic doc first and then refresh this summary.
Labby is centered on the current gateway/operator surface:
search and execute.labby proxy /path/to/dist.js and expose its unmodified MCP surface over loopback or an owned Tailscale Serve HTTPS port with tailnet, bearer, OAuth, or explicit no-auth policy.$LABBY_HOME.~/.labby, provision the host service, and run a health audit across env, reachability, auth, and versions.labby serve log stream.Use the generated service, action, and CLI catalogs below for the complete current product surface instead of copying inventories into hand-written documentation. Standalone ACP chat, Marketplace/MCP Registry browser, Fleet, Deploy, and the old Agent Artifact Manager (Stash) remain retired; current Linux principal-scoped File Stash is a separate contract. Bounded provider-backed discovery through the artifacts control-plane service does not restore those products.
Download the reviewed installer snapshot over canonical HTTPS, then run it locally:
curl --proto '=https' --proto-redir '=https' --tlsv1.2 -fSLo labby-install.sh \
https://raw.githubusercontent.com/dinglebear-ai/labby/5ee609bb255bebfbd9eef4d805998ac1e084b878/scripts/install.sh sh labby-install.sh
This initial script is trusted through canonical HTTPS delivery and the explicitly reviewed commit snapshot above; the download does not follow a mutable branch. Its reviewed, embedded SHA-256 pins authenticate the verifier bootstrap; the installer never downloads a replacement checksum to decide which verifier to trust. It uses an installed GitHub CLI 2.102.0 or newer, or downloads and verifies pinned 2.102.0 into a private temporary directory. It does not change your PATH or install that helper globally. Required system tools are curl, tar, and sha256sum or shasum; macOS bootstrap also uses unzip.
Labby release archives still require checksum and provenance verification against the exact repository, release workflow, immutable tag and hosted-runner policy. Releases with .sigstore.jsonl bundles need no GitHub account: verification runs without tokens and with an empty credential store. Older releases without bundles require your own GitHub authentication; the installer stops before downloading their archive if authentication is unavailable. No privileged credential is supplied or shared. Installing a binary does not establish complete onboarding; the subsequent product-owned setup checks remain required.
The recommended local setup uses a native service, loopback listener, generated protected credentials, and a short-lived browser handoff. In Settings, connect your Agent provider, choose a discovered model and complete a starter Agent test, register selected supported clients, then use Discover to add and verify an MCP server. Required failures remain visible and resumable; installation alone is not full readiness. No manual configuration-file edits are needed on this path.
The checked-in install-labby skill helps with guided installation, advanced deployments, and repair. It is optional. To add it to a skill-aware agent:
npx skills add https://github.com/dinglebear-ai/labby --skill install-labby
$install-labby
The skill inspects the selected host, follows binary-owned setup operations, helps with explicitly requested advanced deployment choices, and verifies the same required first-use checks. Built-in Agent configuration and external-client registration are separate steps. Security-sensitive durable writes remain owned by the Labby binary.
See skills/install-labby/SKILL.md for the canonical APM orchestration skill and docs/adr/0001-install-labby-first-class-install-orchestrator.md for the architecture decision.
Teams that standardize on the Agent Package Manager get the skills and the MCP registration in one step:
apm install -g dinglebear-ai/labby
That deploys install-labby, using-labby, using-codemode, and using-snippets into ~/.claude/skills and ~/.agents/skills and registers the labby stdio MCP server (npx -y @dinglebear/labby mcp) for Claude Code and Codex; apm.yml at the repository root is the manifest and apm outdated -g reports new releases. APM does not install the labby binary or provision a gateway host: use the standalone installer above and labby setup for that. The optional $install-labby skill can guide those steps.
For independent verification of the installer itself, use GitHub CLI 2.102.0 or newer. Older versions are rejected by Labby's installer and release gates because they lack the corrected signer and source-ref verification policy. Public provenance bundles allow this verification without GitHub login; legacy attestation lookup requires your own gh auth login or GH_TOKEN.
Linux/macOS:
Release compatibility gate: select a release that publishes
labby-install.shand contains the documented first-runlabby setup --role ...interface. Confirm the selected tag exposes the installer and checksum before continuing; do not assume an older release matches the current setup contract.
version=vX.Y.Z
base="https://github.com/dinglebear-ai/labby/releases/download/$version" curl -fSLO "$base/labby-install.sh" curl -fSLO "$base/labby-install.sh.sha256"
curl -fSLO "$base/labby-install.sh.sigstore.jsonl" gh attestation verify labby-install.sh \ --bundle labby-install.sh.sigstore.jsonl \ --repo dinglebear-ai/labby \ --signer-workflow dinglebear-ai/labby/.github/workflows/release.yml \ --source-ref "refs/tags/$version" \ --deny-self-hosted-runners shasum -a 256 -c labby-install.sh.sha256 LABBY_INSTALL_VERSION="$version" sh ./labby-install.sh
MCP clients that prefer npm launchers can run Labby through the Node wrapper:
npx -y @dinglebear/labby mcp
The npm launcher is a weaker trust path than the installer scripts. It downloads the release archive for the current platform and verifies only the .sha256 sidecar (or the SHA256SUMS manifest) published next to it on the same release; it does not require gh and does not verify GitHub build provenance. Use labby-install.sh on Linux or macOS when provenance verification matters. Current releases do not publish Windows binaries or installers. The Windows installer source uses the same reviewed verifier pins, protected temporary extraction, and account-free bundle policy; Windows runtime qualification is still required before a Windows release claim.
The separately downloaded and attested install scripts resolve an immutable GitHub Release containing the current platform asset, prepare a verified GitHub CLI, verify the archive's attestation against the Labby repository, release.yml, exact tag, and hosted-runner policy, verify its checksum, and install labby onto the user PATH. The shell installer then runs labby setup, which asks whether this machine should run a server or connect to an existing one. Server setup configures authentication and a managed native service, or an Incus container on supported Linux hosts. Client setup saves the explicit gateway URL and configures browser sign-in or a bearer token. Desktop installation is optional and off by default; if the published desktop package is unavailable, setup reports that and still completes. For Labby's supported ChatGPT web connection, configure the server in OAuth mode and expose it through a publicly reachable HTTPS LABBY_PUBLIC_URL; bearer-only mode is for local/CLI clients and is not the supported ChatGPT web path. The web UI offers bearer token sign-in only over HTTPS or a direct loopback connection; behind a TLS-terminating proxy, set LABBY_PUBLIC_URL=https://... to unlock it.
For unattended shell installs, set LABBY_SETUP_ROLE=server or client and the corresponding LABBY_SETUP_* options. For a binary-only install, set LABBY_INSTALL_NO_SETUP=1. Manual and automatic labby host update operations always skip first-run setup. See the setup guide for examples.
Override install behavior with LABBY_INSTALL_DIR, LABBY_INSTALL_VERSION, or LABBY_INSTALL_REPO. Source fallback is off by default. Opt in with LABBY_ALLOW_SOURCE_FALLBACK=1; a pinned LABBY_INSTALL_VERSION is passed to Cargo as the exact tag instead of silently building the default branch.
Each successful install retains the verified binary by SHA-256 plus an owner-only receipt beneath /.labby-install/. At least the prior verified artifact remains available when distribution is unavailable. Restore it without downloading or changing $LABBY_HOME:
LABBY_INSTALL_ROLLBACK=1 sh ./labby-install.sh
Rollback switches only the installed executable and receipt. It does not downgrade or delete configuration, credentials, databases, or other durable state. Inspect the receipt at /.labby-install/receipt.
Release qualification can install an already-downloaded candidate without network or source fallback by setting LABBY_INSTALL_LOCAL_BINARY and its exact lowercase LABBY_INSTALL_LOCAL_SHA256. The installer copies that input once to private staging, verifies the
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