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Launch Engine — Business Execution OS

by ZionHopkinsversion 1.1.0i★ –iRuns on your computer
Registry nameio.github.ZionHopkins/launch-engine

Install

Overview

Description from the maker (original English)

Agentic pipeline — 39 tools from idea to revenue for solo founders.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: LAUNCH_ENGINE_PROJECT_DIR

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "launch-engine": {
      "command": "npx",
      "args": [
        "-y",
        "launch-engine-mcp"
      ],
      "env": {
        "LAUNCH_ENGINE_PROJECT_DIR": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add launch-engine --env LAUNCH_ENGINE_PROJECT_DIR=your-value -- npx -y launch-engine-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "launch-engine": {
      "command": "npx",
      "args": [
        "-y",
        "launch-engine-mcp"
      ],
      "env": {
        "LAUNCH_ENGINE_PROJECT_DIR": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "launch-engine": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "launch-engine-mcp"
      ],
      "env": {
        "LAUNCH_ENGINE_PROJECT_DIR": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • LAUNCH_ENGINE_PROJECT_DIR env
    Path to your project directory where pipeline-state.json and assets/ live

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account ZionHopkins, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32683 servers in this category
  • Published to the registry more recently than 5% of the other 32683 servers in this category
  • Basic checks equal to or better than 100% of the other 32683 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Launch Engine — Business Execution OS safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.1.0) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, MCP Server Autocad Lisp Helper

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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

Runs in the cloud★ 211Updated 2 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Asset Factory

Agentic pipeline that transforms ideas to revenue — for solo founders and bootstrappers.

npx -y asset-factory-mcp

Why Asset Factory?

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.

  • No more blank-page paralysis. Start with scout and the system tells you exactly what to do next, every step of the way.
  • Every stage feeds the next. Buyer research flows into offer design. Offer design flows into campaign copy. Campaign copy flows into validation. Nothing is wasted.
  • Math before assets. Unit economics are validated before you build anything. You'll never spend weeks building an offer that can't work at your budget.
  • Test ideas for $50, not $5,000. rapid_test gives you signal in 3-5 days with a landing page and paid traffic — before you commit to the full pipeline.
  • Your AI becomes a co-founder, not a chatbot. It doesn't just answer questions. It executes a structured business system with you.

Install

npm install -g asset-factory-mcp

Or run directly without installing:

npx -y asset-factory-mcp

Quick Start

Claude Desktop

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" } } } }

Cursor

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" } } } }

From Source
git clone https://github.com/ZionHopkins/asset-factory-mcp.git

cd asset-factory-mcp npm install npm run build node dist/index.js

How It Works

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.

The Pipeline

Five entry points:
  1. scout → Full pipeline (research → offer → build → deploy → validate)
  2. rapid_test → Quick $50-100 test (signal in 3-5 days)
  3. passive_deploy → Marketplace assets (after research)
  4. tournament → Batch-evaluate 3-5 ideas through Layer 1 simultaneously
  5. portfolio_triage → Rank existing pipelines by profit velocity, select top N
Full Pipeline Flow
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.

Tools Reference

SOP Tools (42)
ToolDescriptionPrerequisites
scoutMarket scanning — takes a raw idea, determines viabilityNone (entry point)
autonomyAgent Autonomy Score — AI-buildable product viabilityscout
market_intelDeep market research with competitive scoringscout, autonomy
researchTherapeutic Buyer Engine — deep persona researchmarket_intel
build_blocks7 Building Blocks from buyer researchresearch
stress_testOffer scoring across 10 dimensionsbuild_blocks
unit_economicsCPA, LTV, break-even modelingstress_test
name_lockLock business/product namestress_test, unit_economics
platformTech stack selection and scoringstress_test
productProduct architecture designstress_test, name_lock
deploySales pages, emails, ad copy generationname_lock, platform, product
qa7-check persona alignment gatedeploy
validate_prepValidation deployment packagedeploy, qa
validate_checkDaily 60-second health checkvalidate_prep
validate_decideEnd-of-window verdictvalidate_prep
feedbackPerformance diagnosis and fix routingdeploy
traffic_strategyTraffic channel research and scoringdeploy
channelsChannel setup and configurationtraffic_strategy
creative_testAd creative variation testingchannels
funnel_optimizeCRO testing across conversion funnelchannels
scaleSystematic scaling of validated channelscreative_test
traffic_analyticsPerformance reporting and attributionchannels
dream_100Relationship strategy and outreachresearch
passive_deployMarketplace asset scoring and specsresearch
passive_checkScheduled performance checkspassive_deploy
passive_compoundDeploy related assets around anchorspassive_deploy
passive_portfolioQuarterly portfolio reviewpassive_deploy
rapid_testQuick idea test — landing page + adsNone (entry point)
rapid_checkDaily metrics vs. thresholdsrapid_test
rapid_graduateGraduate test to full pipelinerapid_check
rapid_statusDashboard of all rapid testsNone
statusPipeline status reportNone
daily_check5-minute daily operations pulseLive campaigns
lessonsPattern library — capture and retrieveNone
voice_extractBrand voice extraction from contentqa
content_engineTopic cluster research, SEO/GEO content generationqa, validate_prep
content_repurposeSingle-pass multi-platform content repurposingcontent_engine
seo_checkMonthly SEO/GEO audit with AI citation trackingcontent_engine
tournamentBatch-evaluate 3-5 ideas through Layer 1None (entry point)
bold_actionBold Action Playbook — highest-leverage irreversible credibility moveqa
portfolio_triageRank pipelines by Profit Velocity Score, enforce active capNone (entry point)
revenue_reviewWeekly revenue phase assessment (Signal → Cash → Repeat → Scale)None (entry point)
Utility Tools (3)
ToolDescription
update_pipeline_stateUpdate pipeline-state.json with dot-notation paths
save_assetSave files to assets/[market-name]/ directory
capture_learningCapture reusable patterns to learnings.json

Project Directory Structure

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

Configuration

The project directory is resolved in order:

  1. ASSET_FACTORY_PROJECT_DIR environment variable
  2. --project-dir= CLI argument
  3. Current working directory

First Use

When 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)

Best Practices

Getting Started
  • Start with `status` — always run this first. It reads your pipeline state and tells you exactly where you are and what to do next.
  • New idea? Use `rapid_test` first — don't run the full pipeline on an unvalidated idea. Spend $50-100 to get signal in 3-5 days. If it graduates, then run scout.
  • One pipeline at a time — you can run multiple rapid tests in parallel, but focus on one full pipeline at a time. Context switching kills momentum.
During the Pipeline
  • Follow the order — the prerequisite system exists for a reason. Each stage feeds the next. Skipping market_intel means research has no competitive context. Skipping stress_test means you might build assets for a broken offer.
  • Don't skip `qa` — it catches promise-product misalignment, unattributed statistics, and persona drift. Every asset that touches a buyer must clear the QA gate.
  • Run `daily_check` every day during validation — it takes 60 seconds and catches problems before they burn budget.
  • Use `lessons` after every major decision — verdicts (ADVANCE/KILL), graduated rapid tests, creative test winners. The pattern library makes every future pipeline smarter.
Working with the AI
  • Let the AI execute the full SOP — each tool returns complete instructions. Don't interrupt midway. Let it finish the research, generate the deliverables, and save the files.
  • Review Tier 3/4 decisions carefully — the system will pause and ask for your input on market selection, pricing, kill decisions, and anything involving real money. These pauses are intentional.
  • Trust the math — 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.
Scaling
  • Validate before you scale — scale requires proven creative winners with 30+ conversions. Scaling unvalidated campaigns is the fastest way to burn money.
  • Compound your learnings — passive assets that reach ANCHOR status should trigger passive_compound. One proven asset can spawn 5-10 related assets.
  • **Run traffic_analytics w

Only the beginning is shown; read the rest in the repo

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