原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Labby

作者:dinglebear-ai版本 2.6.2i★ –i在你的电脑上运行
注册名称ai.dinglebear/labby

安装

概览

作者提供的说明(英文原文)

Rust MCP gateway with Code Mode, authentication, setup, logs, CLI, HTTP API, and operator web UI.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: LABBY_VERSION, LABBY_REPO, LABBY_LOG

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "labby": {
      "command": "npx",
      "args": [
        "-y",
        "@dinglebear/labby",
        "mcp"
      ],
      "env": {
        "LABBY_VERSION": "your-value",
        "LABBY_REPO": "your-value",
        "LABBY_LOG": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add labby --env LABBY_VERSION=your-value --env LABBY_REPO=your-value --env LABBY_LOG=your-value -- npx -y @dinglebear/labby mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "labby": {
      "command": "npx",
      "args": [
        "-y",
        "@dinglebear/labby",
        "mcp"
      ],
      "env": {
        "LABBY_VERSION": "your-value",
        "LABBY_REPO": "your-value",
        "LABBY_LOG": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "labby": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@dinglebear/labby",
        "mcp"
      ],
      "env": {
        "LABBY_VERSION": "your-value",
        "LABBY_REPO": "your-value",
        "LABBY_LOG": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • LABBY_VERSION env
    Optional GitHub release tag override for the downloaded Labby binary.
  • LABBY_REPO env
    Optional GitHub owner/repo override for release asset downloads.
  • LABBY_LOG env
    Tracing filter for Labby runtime logs.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 dinglebear.ai 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32476 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32476 个服务器的 59% 更新
  • 基础检查结果等于或优于此分类中其他 32476 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Labby 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.6.2)于27天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, zanadir

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211昨天更新
安装

zanadir

作者:MustacheCase

Find what a repository's CI is missing, and which security checks cannot fail the build.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Labby

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.

Contents

  • What Labby Does
  • Quick Start
  • Core Workflows
  • Runtime Surfaces
  • Configuration
  • Current Catalogs
  • Architecture
  • Development
  • Documentation

What Labby Does

Labby is centered on the current gateway/operator surface:

  • MCP gateway - connect HTTP and stdio upstream MCP servers, inspect their tools/resources/prompts, apply exposure filters, publish protected MCP routes, and optionally collapse the upstream catalog into Code Mode search and execute.
  • Direct stdio proxy - launch one stdio MCP server with 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.
  • Authentication and protected routes - run bearer or OAuth authentication, manage route-scoped access, authorize upstream OAuth connections, and publish protected MCP endpoints.
  • Code Mode snippets - author, store, and run reusable JavaScript snippets against the upstream catalog, with artifacts persisted under $LABBY_HOME.
  • Setup and doctor - bootstrap ~/.labby, provision the host service, and run a health audit across env, reachability, auth, and versions.
  • Filesystem service - scoped, path-safety-checked file operations exposed through the same action dispatch as every other service.
  • Server logs - search and tail the local labby serve log stream.
  • Incus and bare-metal setup - provision and operate a dedicated Labby gateway host without introducing a separate fleet or deployment product.
  • Generated discovery - publish code-owned service, action, environment, proxy configuration, API route, OpenAPI, MCP help, CLI help, and feature-matrix artifacts under docs/generated.

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.

Quick Start

Install Labby

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.

Optional agent-assisted guidance

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.

Install through APM

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.

Manual Verified Release

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.sh and contains the documented first-run labby 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"

For releases publishing bundles; older releases require authenticated verification.

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

只显示了开头部分;其余内容请在仓库中阅读

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