Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Agentic pipeline — 39 tools from idea to revenue for solo founders.
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.
LAUNCH_ENGINE_PROJECT_DIRNecesitas
¿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": {
"launch-engine": {
"command": "npx",
"args": [
"-y",
"launch-engine-mcp"
],
"env": {
"LAUNCH_ENGINE_PROJECT_DIR": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add launch-engine --env LAUNCH_ENGINE_PROJECT_DIR=your-value -- npx -y launch-engine-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"launch-engine": {
"command": "npx",
"args": [
"-y",
"launch-engine-mcp"
],
"env": {
"LAUNCH_ENGINE_PROJECT_DIR": "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": {
"launch-engine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"launch-engine-mcp"
],
"env": {
"LAUNCH_ENGINE_PROJECT_DIR": "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.
LAUNCH_ENGINE_PROJECT_DIR 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 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub ZionHopkins, 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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
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 (1.1.0) llegó al registro hace 7 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, sync. labs
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
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.
Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.
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.
Agentic pipeline that transforms ideas to revenue — for solo founders and bootstrappers.
npx -y asset-factory-mcp
Most MCP servers give you one tool. A GitHub integration. A database query. A Slack bot.
Asset Factory gives you 42 tools that work as a pipeline — the entire playbook from raw idea to validated revenue, running inside the AI client you already use.
scout and the system tells you exactly what to do next, every step of the way.rapid_test gives you signal in 3-5 days with a landing page and paid traffic — before you commit to the full pipeline.npm install -g asset-factory-mcp
Or run directly without installing:
npx -y asset-factory-mcp
Add to your claude_desktop_config.json:
{
"mcpServers": { "asset-factory": { "command": "npx", "args": ["-y", "asset-factory-mcp"], "env": { "ASSET_FACTORY_PROJECT_DIR": "/path/to/your/project" } } } }
Add to your MCP settings (.cursor/mcp.json):
{
"mcpServers": { "asset-factory": { "command": "npx", "args": ["-y", "asset-factory-mcp"], "env": { "ASSET_FACTORY_PROJECT_DIR": "/path/to/your/project" } } } }
git clone https://github.com/ZionHopkins/asset-factory-mcp.git
cd asset-factory-mcp npm install npm run build node dist/index.js
Asset Factory is a two-layer tool system:
Layer A — 42 SOP Tools (read-only): Each tool validates prerequisites against pipeline-state.json, loads upstream context from previous stages, checks learnings.json for patterns, and returns full SOP instructions enriched with that context. Your AI executes the instructions.
Layer B — 3 Utility Tools (mutations): update_pipeline_state, save_asset, capture_learning. These handle all state writes and file creation. Your AI calls them after executing each SOP.
Five entry points:
LAYER 1 (Strategist):
scout → autonomy → market_intel → research → build_blocks → stress_test → unit_economics
LAYER 2 (Builder): name_lock → platform + product → deploy → qa → validate_prep
LAYER 3 (Validator): validate_check (daily) → validate_decide → feedback → iterate
TRAFFIC (Paid): traffic_strategy → channels → creative_test → funnel_optimize → scale
ORGANIC GROWTH (runs parallel with paid): content_engine → content_repurpose → seo_check (monthly)
BOLD ACTION (post-QA): bold_action → credibility compression playbook
REVENUE PHASE MANAGEMENT (optional overlay): portfolio_triage → revenue_review (weekly) Phases: Signal → Cash → Repeat → Scale
CROSS-CUTTING: status | daily_check | lessons | voice_extract | dream_100 | tournament
Each tool checks prerequisites automatically. If you try to run research before completing market_intel, you'll get a clear STAGE_BLOCKED message telling you exactly what to run first.
| Tool | Description | Prerequisites |
|---|---|---|
scout | Market scanning — takes a raw idea, determines viability | None (entry point) |
autonomy | Agent Autonomy Score — AI-buildable product viability | scout |
market_intel | Deep market research with competitive scoring | scout, autonomy |
research | Therapeutic Buyer Engine — deep persona research | market_intel |
build_blocks | 7 Building Blocks from buyer research | research |
stress_test | Offer scoring across 10 dimensions | build_blocks |
unit_economics | CPA, LTV, break-even modeling | stress_test |
name_lock | Lock business/product name | stress_test, unit_economics |
platform | Tech stack selection and scoring | stress_test |
product | Product architecture design | stress_test, name_lock |
deploy | Sales pages, emails, ad copy generation | name_lock, platform, product |
qa | 7-check persona alignment gate | deploy |
validate_prep | Validation deployment package | deploy, qa |
validate_check | Daily 60-second health check | validate_prep |
validate_decide | End-of-window verdict | validate_prep |
feedback | Performance diagnosis and fix routing | deploy |
traffic_strategy | Traffic channel research and scoring | deploy |
channels | Channel setup and configuration | traffic_strategy |
creative_test | Ad creative variation testing | channels |
funnel_optimize | CRO testing across conversion funnel | channels |
scale | Systematic scaling of validated channels | creative_test |
traffic_analytics | Performance reporting and attribution | channels |
dream_100 | Relationship strategy and outreach | research |
passive_deploy | Marketplace asset scoring and specs | research |
passive_check | Scheduled performance checks | passive_deploy |
passive_compound | Deploy related assets around anchors | passive_deploy |
passive_portfolio | Quarterly portfolio review | passive_deploy |
rapid_test | Quick idea test — landing page + ads | None (entry point) |
rapid_check | Daily metrics vs. thresholds | rapid_test |
rapid_graduate | Graduate test to full pipeline | rapid_check |
rapid_status | Dashboard of all rapid tests | None |
status | Pipeline status report | None |
daily_check | 5-minute daily operations pulse | Live campaigns |
lessons | Pattern library — capture and retrieve | None |
voice_extract | Brand voice extraction from content | qa |
content_engine | Topic cluster research, SEO/GEO content generation | qa, validate_prep |
content_repurpose | Single-pass multi-platform content repurposing | content_engine |
seo_check | Monthly SEO/GEO audit with AI citation tracking | content_engine |
tournament | Batch-evaluate 3-5 ideas through Layer 1 | None (entry point) |
bold_action | Bold Action Playbook — highest-leverage irreversible credibility move | qa |
portfolio_triage | Rank pipelines by Profit Velocity Score, enforce active cap | None (entry point) |
revenue_review | Weekly revenue phase assessment (Signal → Cash → Repeat → Scale) | None (entry point) |
| Tool | Description |
|---|---|
update_pipeline_state | Update pipeline-state.json with dot-notation paths |
save_asset | Save files to assets/[market-name]/ directory |
capture_learning | Capture reusable patterns to learnings.json |
Asset Factory creates and manages files in your project directory:
your-project/
├── pipeline-state.json # Pipeline progress tracking ├── learnings.json # Pattern library across pipelines └── assets/ └── [market-name]/ ├── research/ # Scout reports, buyer research, market intel ├── building-blocks/ # The 7 Building Blocks ├── product/ # Product Architecture Blueprint ├── copy/ # Sales letters, email sequences ├── campaigns/ # Landing pages, ad copy ├── traffic/ # Traffic strategy, creative tests, analytics ├── validation/ # Deployment packages, daily checks, verdicts ├── voice/ # Brand voice calibration ├── passive-portfolio/ # PADA outputs ├── rapid-test/ # Rapid test assets ├── bold-action/ # Bold Action playbook └── content/ # Organic growth engine outputs ├── pillar/ # 2,000-4,000 word guides ├── spokes/ # 1,000-2,000 word pages ├── repurposed/ # Multi-platform assets per source ├── schema/ # JSON-LD files ├── seo-config/ # robots.txt, sitemap, brand signals └── audits/ # Monthly SEO/GEO audit reports
The project directory is resolved in order:
ASSET_FACTORY_PROJECT_DIR environment variable--project-dir= CLI argumentWhen you run status with no existing pipeline, you'll see:
Three paths available:
1. rapid_test — $50-100 paid traffic test in 3-5 days
2. scout — Full active pipeline with deep research and validation
3. passive_deploy — Marketplace assets (requires research first)
scout.market_intel means research has no competitive context. Skipping stress_test means you might build assets for a broken offer.unit_economics will tell you if the numbers work at your budget. If the verdict is NON-VIABLE, don't try to force it. Move on or adjust the offer.scale requires proven creative winners with 30+ conversions. Scaling unvalidated campaigns is the fastest way to burn money.passive_compound. One proven asset can spawn 5-10 related assets.traffic_analytics wSolo se muestra el principio; lee el resto en el repo