GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Descripción del creador (original en inglés)
Impact analysis, architecture rules and a tamper-evident ledger for AI coding agents.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
DATABASE_URL, GARUDA_WORKSPACELos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en 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"
}
}
}
}Ejecuta esto en tu terminal
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:1.9.11Completa los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
GARUDA_WORKSPACE envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub myshra777-ai, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: DATABASE_URL
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.9.11) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Docker en tu computadora.
En la misma categoría: GitHub, Desktop Commander, Cloudflare MCP
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
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:
Know the impact. Enforce the rules. Keep the evidence.
Works with Go, Python, TypeScript, and Java (Beta), with more languages on the way.
Say your assistant is asked to add a feature to the payment handler.
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).
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.)
./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 problem | Why it matters |
|---|---|
| The payment handler talks to the database directly | Skips 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 layer | Dependencies 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.
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 see | It means |
|---|---|
| ALLOW / WARN / REVIEW / BLOCK | The verdict on a change. BLOCK stops it and tells the assistant how to repair it. |
| SUPPORTED | The evidence backs this claim, within what was checked. Safe to rely on. |
| UNVERIFIED | Found in the code or docs but not confirmed yet. Not an error. |
| CONTRADICTED | The evidence conflicts with a rule or claim you wrote down. |
| HIGH / MEDIUM / LOW tier | How many things depend on this code. High-tier code is protected from silent AI rewrites. |
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.
garuda init sets this up automatically for Claude Code, Claude Desktop and Cursor. To install it as a plugin instead:
| Tool | How |
|---|---|
| Claude Code | /plugin marketplace add myshra777-ai/garuda then /plugin install garuda@garuda |
| OpenAI Codex | codex plugin marketplace add myshra777-ai/garuda |
| Cursor | Run garuda init; it writes the rules and MCP settings into your project (.cursor-plugin/ has the plugin manifest) |
| Anything that speaks MCP | Run 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:
| Skill | When the assistant uses it |
|---|---|
pre-edit-governance | Before changing code: proceed, revise or ask a human? |
change-impact | Who calls this, and how far does the damage spread? |
post-edit-verification | After the edit: any new violations in this diff? |
violation-repair | A change was blocked; fix it without breaking something else |
architecture-review | Does the real code match the documented design? |
evidence-verification | Is this claim backed by code, and is the receipt genuine? |
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:
.github/workflows/garuda-gate.yml, you also get a verdict comment on the pull request and findings in GitHub's Security tab;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.
Solo se muestra el principio; lee el resto en el repo