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。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Garuda

作者:myshra777-ai版本 1.9.11i★ –i在你的电脑上运行
注册名称io.github.myshra777-ai/garuda

安装

概览

作者提供的说明(英文原文)

Impact analysis, architecture rules and a tamper-evident ledger for AI coding agents.

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: 开发者工具
  • 你需要填写:DATABASE_URL

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: DATABASE_URL, GARUDA_WORKSPACE

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

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": {
    "garuda": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "GARUDA_WORKSPACE",
        "ghcr.io/myshra777-ai/garuda-mcp:1.9.11"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "GARUDA_WORKSPACE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add garuda --env DATABASE_URL=your-value --env GARUDA_WORKSPACE=your-value -- docker run -i --rm -e DATABASE_URL -e GARUDA_WORKSPACE ghcr.io/myshra777-ai/garuda-mcp:1.9.11

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": {
    "garuda": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "GARUDA_WORKSPACE",
        "ghcr.io/myshra777-ai/garuda-mcp:1.9.11"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "GARUDA_WORKSPACE": "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": {
    "garuda": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "GARUDA_WORKSPACE",
        "ghcr.io/myshra777-ai/garuda-mcp:1.9.11"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "GARUDA_WORKSPACE": "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

  • DATABASE_URL 机密 必填 env
    PostgreSQL connection URL for the Garuda graph and ledger
  • GARUDA_WORKSPACE env
    Workspace name to govern

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 myshra777-ai 验证,该账户拥有此仓库

  • … 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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 5541 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5541 个服务器的 78% 更新
  • 基础检查结果等于或优于此分类中其他 5541 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

Garuda 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?

你需要填写:DATABASE_URL

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(1.9.11)于5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 Docker。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

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:↓ 每周下载量i★ 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

GitHub

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

作者:github广泛使用★ 3.4万5天前更新

电脑或云端

Desktop Commander

MCP server for terminal commands, file operations, and process management

作者:wonderwhy-er广泛使用↓ 71万/周★ 1万17天前更新

在你的电脑上运行

Cloudflare MCP

Cloudflare MCP servers

作者:cloudflare广泛使用★ 444614个月前更新

在云端运行✓ mcp.cloudflare.com

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。

Garuda

AI can write the code. Garuda makes sure the change respects your system.

Change control for AI-written code.

Leading an engineering team? The business case in two minutes →

▶ Watch the dashboard demo video


What is this?

You let an AI assistant (Claude Code, Cursor, Codex…) change your code. It works. The tests pass. But did it quietly skip your service layer, break a rule your team agreed on last year, or change a number your finance team relies on?

Your assistant is good at writing code. It does not automatically know every decision your team made, every part of the system that depends on the code, or every rule that has to stay true.

Garuda is a safety check that sits between your AI assistant and your codebase:

  1. Before the assistant edits something, Garuda tells it who depends on that code and which rules apply.
  2. After the edit, Garuda checks the change against your rules and says allow, warn, review or block, with plain instructions for fixing it.
  3. Saved decisions are sealed into a tamper-evident log, so you can prove later what was checked and when.

Know the impact. Enforce the rules. Keep the evidence.

Works with Go, Python, TypeScript, and Java (Beta), with more languages on the way.

One change, start to finish

Say your assistant is asked to add a feature to the payment handler.

  1. It asks Garuda first. Garuda replies: "12 other things depend on this. It is high-risk code. Rule: the payment handler must not talk to the database directly."
  2. The assistant makes its edit. In a hurry, it calls the database straight from the handler.
  3. Garuda checks the change. It sees the broken rule, says BLOCK, and tells the assistant exactly what to move and where.
  4. The assistant fixes it. The second check says ALLOW.
  5. The result is saved. You get a receipt you can look up later.

Garuda also separates problems this change introduced from problems that were already there. You are not asked to clean up years of old code before you can move forward. You only answer for what is new.

It reads Go with the compiler's full type checker (go/types), and its Beta Python, TypeScript, and Java analyzers resolve cross-file imports (__init__.py, barrel index.ts, tsconfig.json @/* paths, JAVA_IMPORT package/static imports), import aliases, type annotations (Optional[T], Promise , CompletableFuture ), constructor fields (self.attr / private readonly / Spring @Autowired DI), interface implementations, inheritance (super()), and return-type method calls at 0.95 confidence with exact file and line evidence (see What Garuda does not do).


Take the tour (about 10 minutes)

1. Install it · *3 minutes*
git clone https://github.com/myshra777-ai/garuda.git

cd garuda ./setup.sh

setup.sh starts a local PostgreSQL database, builds the tools into bin/, and starts the dashboard. It prints your login at the end. On Windows use setup.ps1.

Just want to look first? npx garuda-guard demo runs the demo below with no database (needs Node 18 or newer). Prefer to let an AI assistant do it? Copy a prompt for ChatGPT, Claude, Codex or Cursor.

Prefer one line? curl -fsSL https://raw.githubusercontent.com/myshra777-ai/garuda/main/install.sh | bash does the same. (As with any installer you pipe into a shell, read it first.)

2. Watch it catch three planted bugs · *1 minute*
./bin/garuda demo

This builds a tiny fake payments service with three problems planted on purpose, runs Garuda's analyzer on it, and lists the problems Garuda is built to catch. It needs no database:

Planted problemWhy it matters
The payment handler talks to the database directlySkips the layer that is supposed to guard money movement
Money is calculated with float64, and one report is off by 10× (48 Cr vs 4.8 Cr)Silent wrong numbers
The storage layer imports the payment layerDependencies pointing the wrong way

You'll see each problem, the exact file and line, and a short "how to fix it" an AI assistant can follow. The service and its three problems are made up for the demo, and the demo lists them rather than detecting them. To see real detection on real code, finish step 1 and run garuda check in step 4. On Windows, run .\bin\garuda.exe demo.

3. Open the dashboard · *2 minutes*

Go to http://localhost:8080/login and sign in with the login setup.sh printed.

The dashboard's front page walks you through five steps. Here is what each part gives you:

Add your own project. Click New Workspace, paste a GitHub link or a folder path, and Garuda reads the code for you.

See your system without the spaghetti. Instead of one giant tangled graph, Garuda shows the small neighbourhood around the thing you care about: who calls it, and what it calls.

Turn written decisions into enforced rules. Drop in your design docs or decision records (ADRs). Garuda pulls out the "must" and "must not" lines and links them to the code they talk about. No docs yet? It drafts a rulebook from your code for you to approve.

Spot numbers that disagree. When two teams calculate the same metric differently, or one query divides by 1e7 and another by 1e8, Garuda helps you line up the two versions, shows the formulas it found in the code, and asks a human to decide which one is right. It does not guess.

Learn the signals. Every badge has one fixed meaning:

You seeIt means
ALLOW / WARN / REVIEW / BLOCKThe verdict on a change. BLOCK stops it and tells the assistant how to repair it.
SUPPORTEDThe evidence backs this claim, within what was checked. Safe to rely on.
UNVERIFIEDFound in the code or docs but not confirmed yet. Not an error.
CONTRADICTEDThe evidence conflicts with a rule or claim you wrote down.
HIGH / MEDIUM / LOW tierHow many things depend on this code. High-tier code is protected from silent AI rewrites.
4. Point it at your own code · *3 minutes*
cd /path/to/your/project

/path/to/garuda/bin/garuda init . --wizard # five short questions /path/to/garuda/bin/garuda rulebook generate # drafts rules from your code /path/to/garuda/bin/garuda check . --diff HEAD # checks what you just changed

Not sure which rules to start with? Pick a ready-made set: garuda init . --template layered (also hexagonal, microservices, no-circular-imports, financial, zero-trust-auth, ai-agent-safety, pii-gdpr-hipaa, idempotent-mutations, or all). They live in policies/templates/.

Coming from ArchUnit, Dependency-Cruiser or Import Linter? garuda import --from archunit --input converts your existing rules.

If something looks off, run ./bin/garuda doctor. It checks your database, migrations and hooks and tells you what is wrong.


Plug it into your AI assistant

garuda init sets this up automatically for Claude Code, Claude Desktop and Cursor. To install it as a plugin instead:

ToolHow
Claude Code/plugin marketplace add myshra777-ai/garuda then /plugin install garuda@garuda
OpenAI Codexcodex plugin marketplace add myshra777-ai/garuda
CursorRun garuda init; it writes the rules and MCP settings into your project (.cursor-plugin/ has the plugin manifest)
Anything that speaks MCPRun garuda-mcp over stdio (example config)

The plugin needs the garuda-mcp program and a database, so do step 1 above first.

What your assistant gets: 54 tools (41 read-only, 13 that can change state) and 6 skills, short playbooks that tell it when to use them:

SkillWhen the assistant uses it
pre-edit-governanceBefore changing code: proceed, revise or ask a human?
change-impactWho calls this, and how far does the damage spread?
post-edit-verificationAfter the edit: any new violations in this diff?
violation-repairA change was blocked; fix it without breaking something else
architecture-reviewDoes the real code match the documented design?
evidence-verificationIs this claim backed by code, and is the receipt genuine?

Check every pull request

Your assistant's good behaviour is a request. A pull request check is a rule. Add the GitHub Action and every pull request gets a verdict:

  • the verdict (ALLOW, WARN, REVIEW or BLOCK) and a receipt hash in the run summary, with a one-line command to reproduce it on your machine;
  • a BLOCK fails the check;
  • with the ready-made workflow, .github/workflows/garuda-gate.yml, you also get a verdict comment on the pull request and findings in GitHub's Security tab;
  • optional Slack or Teams alerts through garuda check --notify-slack / --notify-teams.

Copy a ready-to-paste snippet from docs/GITHUB_MARKETPLACE_STRATEGY.md, or use action.yml directly.

One more step makes it real: in your repository go to Settings → Rules (or Branches), and make the Garuda check a required status check. Until you do, a failing check is only a warning that people can merge past.


What Garuda does

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx