Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Rust MCP gateway with Code Mode, authentication, setup, logs, CLI, HTTP API, and operator web UI.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
LABBY_VERSION, LABBY_REPO, LABBY_LOGDu brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"labby": {
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add labby --env LABBY_VERSION=your-value --env LABBY_REPO=your-value --env LABBY_LOG=your-value -- npx -y @dinglebear/labby mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"labby": {
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"labby": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@dinglebear/labby",
"mcp"
],
"env": {
"LABBY_VERSION": "your-value",
"LABBY_REPO": "your-value",
"LABBY_LOG": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
LABBY_VERSION envLABBY_REPO envLABBY_LOG envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde über die Domain dinglebear.ai bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.6.2) kam vor 27 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, AI Deprecations
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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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