REA
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Designs, prices, and deploys AWS/GCP cloud infrastructure from plain-English requirements.
Elige la app de IA que usas y copia la configuración.
Pasó 5/5 revisiones · Lo que preguntas pasa por el servidor del autor (app.luthersystems.com)
Primero: ¿qué IA usas?
Elige tu app y los pasos aparecen abajo.
Funciona con Claude · unos 2 min
Sin clave y sin instalar nada · Configúralo una vez en claude.ai o en la app de escritorio y úsalo en el chat · las cuentas gratis pueden añadir 1 · en Team/Enterprise lo añade un Owner
CustomizeConnectors
Copia cada valor al campo con el mismo nombre en Claude y pulsa Continue
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
Pulsa Continue en la pantalla de inicio de sesión que detectó Claude · en Authentication elige lo que indique el autor (Sign in now, Sign in when needed o No sign in) y pulsa Add
+ConnectorsInsideOut (Riley)
Usa InsideOut (Riley) y dime qué puedes hacer por mí; luego muéstrame una cosa✓ Si Claude dice que está usando InsideOut (Riley) o muestra una herramienta de InsideOut (Riley) en la respuesta, ya está conectado
Nombres de menú comprobados con la ayuda de Anthropic el 11 nov 2026 · tu pantalla puede variar un poco según la versión
Funciona con ChatGPT según tu plan
MCP completo: ChatGPT Business, Enterprise o Edu en la web · Pro: conecta con permisos de lectura/obtención, así que las herramientas que cambian datos pueden no funcionar · Plus: no confirmado en la documentación; si ves una opción para añadir MCP propio en la página de plugins puedes probar · solo web
Plugins+Add custom MCP server
Pon un nombre, pega la dirección en Connection, marca el aviso de riesgo y pulsa Create as a plugin
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
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Abre un chat nuevo y elige InsideOut (Riley) en tus plugins antes de escribir
Usa InsideOut (Riley) y dime qué puedes hacer por mí; luego muéstrame una cosa✓ Si ChatGPT dice que está usando InsideOut (Riley) o muestra una herramienta de InsideOut (Riley) en la respuesta, ya está conectado
Nombres de menú comprobados con la ayuda de OpenAI el 11 nov 2026 · tu pantalla puede variar un poco según la versión
Funciona con Claude Code · unos 2 min
Sin clave y sin instalar nada
Mac: pulsa Command+Espacio y escribe Terminal · Windows: abre PowerShell
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
Deberías ver InsideOut (Riley) en la lista como conectado
Usa InsideOut (Riley) y dime qué puedes hacer por mí; luego muéstrame una cosa✓ Si Claude Code dice que está usando InsideOut (Riley) o muestra una herramienta de InsideOut (Riley) en la respuesta, ya está conectado
Nombres de menú comprobados con la ayuda de Anthropic el 11 nov 2026 · tu pantalla puede variar un poco según la versión
Funciona con Cursor · unos 2 min
Sin clave y sin instalar nada
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
Usa InsideOut (Riley) y dime qué puedes hacer por mí; luego muéstrame una cosa✓ Si Cursor dice que está usando InsideOut (Riley) o muestra una herramienta de InsideOut (Riley) en la respuesta, ya está conectado
Nombres de menú comprobados con la ayuda de Cursor el 11 nov 2026 · tu pantalla puede variar un poco según la versión
Funciona con VS Code · unos 2 min
Sin clave y sin instalar nada
Revisando los comandos · los botones de copiar aparecen cuando pasan la revisión
Usa InsideOut (Riley) y dime qué puedes hacer por mí; luego muéstrame una cosa✓ Si VS Code dice que está usando InsideOut (Riley) o muestra una herramienta de InsideOut (Riley) en la respuesta, ya está conectado
Nombres de menú comprobados con la ayuda de VS Code el 11 nov 2026 · tu pantalla puede variar un poco según la versión
Otras apps que usan MCP, como Windsurf, Zed o Gemini CLI, añaden servidores de forma distinta. Míralo en la lista de apps
Ver todas las apps que usan MCP →
Dirección para apps que se conectan por la web
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La configuración JSON está en “Para desarrolladores”, abajo
Claude Code
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Cursor (~/.cursor/mcp.json)
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VS Code (mcp.json)
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Claude Code
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Claude Desktop (claude_desktop_config.json)
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Cursor (~/.cursor/mcp.json)
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VS Code (mcp.json)
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Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
oci: docker.io/luthersystems/insideout-mcp:v0.36.3Según cómo se conecta este servidor y la documentación de cada app, comprobado el 10 nov 2026.
Se conectan por internet en
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
Se ejecutan en tu computadora en
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Nombres y descripciones de las herramientas tal como los informó el servidor el 10 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.
awsinspectINSPECTION: Inspect AWS infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Insp
awsinspect_batchBATCH INSPECTION: run up to 32 AWS inspect probes in one call. ⚠️ **PREREQUISITE**: Same as awsinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credent
convoawaitWait for a pending response from Riley after a convoreply timeout. 🎯 USE THIS TOOL WHEN: convoreply returned a timeout error. This allows you to continue waiting for the response without resending the message. REQUIRES: - session_id: from convoopen response OPTIONAL: - message_i
convoinspectINSPECTION: View a session's conversation transcript and metadata Returns the full message history (user / assistant / tool turns) plus the session's meta — workflow step, cloud, deployment status, drift state. This is the transcript-reader companion to the other read tools — com
convoopenWORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward t
convoreplyWORKFLOW: Step 2 of 4 - Continue infrastructure design conversation Send a user message to the active InsideOut session and receive the assistant reply. The response contains a clean message from Riley - display it to the user. ⚠️ CRITICAL: DO NOT answer Riley's questions yoursel
convostatusINSPECTION: View the current infrastructure stack for a session Returns the current state of the user's infrastructure design including: **Components** - Selected infrastructure services (VPC, databases, caching, etc.) • Shows what services the user has chosen (e.g., PostgreSQL,
credawaitWait for the user to securely connect their cloud account and subscribe to Luther Systems. Polls until credentials appear on the session. 🎯 USE THIS TOOL WHEN: tfdeploy returns an 'auth_required', 'no_credentials', or 'credentials_expired' error. The user needs to visit the conn
gcpinspectINSPECTION: Inspect GCP infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Insp
gcpinspect_batchBATCH INSPECTION: run up to 32 GCP inspect probes in one call. ⚠️ **PREREQUISITE**: Same as gcpinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credent
helpGet workflow guidance for using InsideOut infrastructure tools. Call help() for a compact overview, or help(section=...) for a detailed guide. Sections: workflow, tools, examples, inspect. Responses include hints with next_actions and related_tools.
stackdiffStructured diff showing what would be deployed if the user ran tfdeploy now. Returns component-level changes (added/removed/modified), field-level details, and pricing deltas. Defaults (#1392): with no version arguments, compares the LAST SUCCESSFULLY DEPLOYED version against the
stackrollbackCreate a draft version by reverting to a previous version's config. Copies components, config, and pricing from the target version. If a draft already exists, updates it in-place (single-draft rule). Use `stackversions` first to find available version numbers. REQUIRES: session_i
stackversionsList all stack versions for a session (newest first). Shows version history including version number, status (draft/confirmed/applied), change summaries, and timestamps. Use this tool to see the design history, review what changed between iterations, or find a version number to r
submit_feedbackFEEDBACK: Submit feedback, bug reports, or feature requests to Luther Systems Use this tool to forward user feedback directly to the Luther Systems team. This includes bug reports, feature requests, questions, or general feedback about InsideOut. The agent itself can also use thi
tfdeployWORKFLOW: Step 4 of 4 - Deploy infrastructure to the cloud Deploy infrastructure by starting a Terraform job for an InsideOut session. This tool initiates the actual deployment process after Terraform files have been generated. IMPORTANT: This starts a long-running job (15+ minut
tfdestroyDESTROY: Tear down previously deployed infrastructure Destroys infrastructure by calling the Oracle destroy endpoint for a session that has a prior successful deployment. IMPORTANT: This starts a long-running job. Use tfstatus/tflogs to monitor progress. SINGLE-FLIGHT: only one T
tfdriftDRIFT CHECK: Run a read-only drift detection check Checks whether deployed infrastructure has drifted from the expected Terraform state. This is a read-only operation — it does NOT modify any infrastructure. Returns job_id. Use tflogs to stream the drift check results. SINGLE-FLI
tfgenerateWORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NO
tflogsMONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with
tfoutputsINSPECTION: Retrieve Terraform outputs from a completed deployment Returns structured output values (VPC IDs, endpoints, cluster names, etc.) after a successful deploy. Sensitive outputs are redacted (shown as '(sensitive)'). By default returns outputs for the latest successful d
tfplanPREVIEW: Run terraform plan to preview infrastructure changes Runs a terraform plan for an InsideOut session without applying any changes. This lets the user review what will be created/changed/destroyed before committing. Returns job_id, plan_id, and project_id. Use tflogs to st
tfrunsINSPECTION: List all Terraform deployment runs for a session Returns job IDs, statuses, types (apply/destroy), and timestamps for every run. Use this to see deployment history, find job IDs for log inspection, or check which deployments succeeded or failed. REQUIRES: session_id f
tfstatusMONITORING: Quick status check for Terraform deployments Check the current status of a Terraform deployment job. Use this tool to quickly check if a deployment is running, completed, or failed. Returns job status, job_id, and other metadata without streaming logs. Use tflogs to s
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 14 nov 2026
El nombre en el registro se verificó con el dominio insideout.luthersystems.com (el registro comprueba quién es dueño del dominio)
Último cambio de código: ayer
Usa Apache-2.0
No hace falta iniciar sesión
Leímos 24 descripciones de herramientas y no encontramos instrucciones ocultas para la IA
Pregunta, comparte un consejo o avisa de que no funciona. Ordenado por lo que la gente marcó como útil.
Aún no hay publicaciones. Sé la primera persona en preguntar o compartir.
Lo publicado aquí lo escriben usuarios, no el equipo de PopNx.
Aún no hay reseñas
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 5 de 5 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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Funciona de las dos formas: instálalo en tu computadora o conéctate a la versión en la nube.
El repo de GitHub cambió por última vez ayer, y la última versión (0.36.3) llegó al registro hace 6 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también sirve en apps que aceptan MCP remoto, como ChatGPT en la web (MCP completo en Business y superiores; Pro solo lectura).
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
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.
Cloud infrastructure automation. Describe your application in natural language and InsideOut will design, configure, deploy, and manage production-ready backend infrastructure -- in minutes, not weeks.
Works standalone or integrated directly into AI app builders via MCP.
npx skills add luthersystems/insideout-agent-skills
Works with Claude Code, Codex, Cursor, Kiro, Windsurf, and 30+ other tools.
[View on Skills.sh](https://skills.sh/luthersystems/insideout-agent-skills/insideout) | [Try the web app](https://insideout.luthersystemsapp.com/) -- no install required.
Setting up cloud infrastructure is slow, error-prone, and requires deep DevOps expertise. Teams spend weeks on plumbing -- networking, security, storage, scaling configuration -- before writing a single line of product code.
InsideOut eliminates this. You describe your application; InsideOut handles the rest: architecture design, Terraform generation, cost estimation, deployment, and ongoing management.
Before InsideOut: Weeks of manual infrastructure setup, Terraform authoring, and cloud configuration. With InsideOut: Backend infrastructure deployed in minutes, managed continuously.
| Capability | Manual Terraform | InsideOut |
|---|---|---|
| Time to deploy | Days to weeks | Minutes |
| Security defaults | Manual | Automatic |
| Cost visibility | Post-deploy billing | Pre-deploy estimates |
| Observability setup | Manual | Day one |
| AI app builder integration | None | Native (Claude Code, Codex, Kiro, Antigravity) |
| Terraform ownership | Yes | Yes (generated, exportable) |
Once installed, just ask:
"Build me a scalable backend for my golang microservices app on AWS with a DB and auth."
InsideOut will:
You: "I need infrastructure for an e-commerce platform, 1k monthly users on AWS"
Riley: "I'd recommend ECS for your containers, RDS PostgreSQL for your database, ElastiCache Redis for sessions, and an ALB. Estimated cost: ~$350/month. Want me to adjust anything?"
You: "Looks good, generate the Terraform"
[Generates production-ready Terraform files]
You: "Deploy it"
[Deploys to AWS, streams logs in real-time]
| User | Use case |
|---|---|
| Solo developers | Ship a production backend without DevOps expertise |
| Startup engineering teams | Move from idea to deployed infrastructure in minutes |
| AI app builders | Integrate infrastructure automation directly into AI-native development workflows |
| Enterprise teams | Standardise infrastructure with best practices and cost controls |
| DevOps / platform engineers | Faster architecture and IaC workflows |
If you'd rather describe what you want than manually wire it together -- this is for you.
| Path | Best for | Install |
|---|---|---|
| This repo (recommended for Codex) | Portable skill across multiple AI tools | npx skills add luthersystems/insideout-agent-skills |
| [Claude Code plugin](https://github.com/luthersystems/insideout-claude-code) | Best native Claude Code experience | /plugin marketplace add luthersystems/insideout-claude-code |
| [Kiro power](https://github.com/luthersystems/insideout-power) | Best native Kiro experience | Add power from GitHub: luthersystems/insideout-power |
| [Web app](https://insideout.luthersystemsapp.com/) | No install required | Open in browser |
npx skills add luthersystems/insideout-agent-skills
For the full plugin experience (slash commands, agents, hooks, auto-approve):
/plugin marketplace add luthersystems/insideout-claude-code
/plugin install insideout
npx skills add luthersystems/insideout-agent-skills --agent codex
Activate by typing $insideout -- Codex will detect the missing MCP server and prompt you to install it automatically.
Fallback: If the auto-install doesn't trigger, run:
codex mcp add insideout --url https://app.luthersystems.com/v1/insideout-mcp
npx skills add luthersystems/insideout-agent-skills --agent cursor
Then add the MCP server to your Cursor MCP config:
{
"mcpServers": { "insideout": { "type": "http", "url": "https://app.luthersystems.com/v1/insideout-mcp" } } }
npx skills add luthersystems/insideout-agent-skills --agent windsurf
Add MCP via Windsurf MCP Marketplace or manually in settings.
For the full power experience (steering files, design pattern guides, auto-approve):
luthersystems/insideout-powernpx skills add luthersystems/insideout-agent-skills --agent antigravity
Then add the MCP server in Antigravity: "..." menu → MCP Servers → Manage MCP Servers → View raw config:
{
"mcpServers": { "insideout": { "serverUrl": "https://app.luthersystems.com/v1/insideout-mcp" } } }
Note: Antigravity uses
serverUrl, noturl.
git clone https://github.com/luthersystems/insideout-agent-skills.git
cp -r insideout-agent-skills ~/.agents/skills/insideout
The ~/.agents/skills/ directory is the standard cross-tool location. Most AI coding tools will detect skills here automatically.
| Category | AWS | GCP |
|---|---|---|
| Compute | EC2, ECS, EKS, Lambda | Compute Engine, Cloud Run, GKE, Cloud Functions |
| Database | RDS PostgreSQL, DynamoDB, ElastiCache, OpenSearch | Cloud SQL, Firestore, Memorystore |
| Networking | VPC, ALB, CloudFront, API Gateway | VPC, Load Balancing, Cloud CDN, API Gateway |
| Storage | S3 | Cloud Storage |
| Security | WAF, KMS, Secrets Manager, Cognito | Cloud Armor, Cloud KMS, Secret Manager, Identity Platform |
| Messaging | SQS, MSK (Kafka) | Pub/Sub |
| Observability | CloudWatch, Managed Grafana | Cloud Logging, Cloud Monitoring |
| AI/ML | Bedrock | Vertex AI |
| CI/CD | CodePipeline, GitHub Actions | Cloud Build |
| Backup | AWS Backup | GCP Backups |
Architecture patterns: AI Stack, Microservices, Serverless. Azure support is upcoming.
Describe your application in natural language. InsideOut generates the architecture, configuration, and Terraform. Review, tweak, and deploy -- all from one place.
Get cost estimates for your exact stack before committing. No surprise bills; pricing is surfaced at design time.
Security best practices applied automatically. Observability configured from day one -- no retroactive setup needed.
You own the generated Terraform files. Use InsideOut defaults or override any setting. No lock-in; the output is standard infrastructure-as-code.
Luther Systems sets up and manages critical infrastructure. Ongoing updates and operational support included.
InsideOut uses a multi-agent AI system behind a single MCP server:
| Agent | Role |
|---|---|
| Riley | Infrastructure advisor -- leads the design conversation |
| Hippo | Cost estimation and pricing optimization |
| Joy | User experience and requirement gathering |
| Etch | Terraform code generation |
| Core | Architecture validation and best practices |
| Axel | Deployment orchestration |
From your perspective, you're talking to Riley. The other agents work behind the scenes. These capabilities are exposed as tools inside your AI environment, so you use them conversationally.
See SECURITY.md for detailed data flow documentation.
InsideOut uses a library of battle-tested, standard Terraform modules composed for common infrastructure patterns.
Can I use InsideOut without the InsideOut UI? Yes. InsideOut integrates with Claude Code, Codex, Kiro, Antigravity, and any MCP-compatible AI development environment, allowing you to design, price, and deploy infrastructure directly from your editor without opening the InsideOut interface.
Do I own the generated Terraform? Yes. InsideOut generates standard Terraform files that you own and can export, modify, or use independently of the platform.
Can I override the default configuration? Yes. InsideOut applies best-practice defaults but every setting is overridable. You control the final configuration before deployment.
What clouds does InsideOut support? AWS and Google Cloud Platform. AWS has the deepest support with the widest range of resource types. Azure support is upcoming.
Is InsideOut suitable for AI application backends? Yes. InsideOut explicitly supports AI stack architectures and is designed to work within AI-native development environments like Claude Code, Codex, Kiro, Antigravity, and other MCP-compatible tools.
How does pricing work? Cost estimates for your exact stack are surfaced before deployment. Contact Luther Systems for platform pricing: contact@luthersystems.com
Luther Systems is an enterprise infrastructure and automation company founded in 2015, headquartered in London, UK. Our mission is to accelerate the advent of the automated enterprise.
Founded by a team who spent years automating complex processes for some of the world's largest financial institutions, Luther Systems builds platforms that bring enterprise-grade infrastructure and operations to teams of every size.