Launch Engine — Business Execution OS

io.github.ZionHopkinsPublished by GitHub account ZionHopkinsv1.1.0Updated Nov 3, 2026

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

The publisher's own server: Execution Market

Overview

AI-generated overview

A local stdio MCP server that walks a solo founder through a staged business launch pipeline, from idea research to paid-traffic validation, using 42 SOP…

What you can do
  • Run staged business playbooks: idea scouting, market research, buyer personas, offer stress tests and unit economics
  • Design and deploy assets: naming, platform and product architecture, sales pages, emails and ad copy, with a QA gate
  • Plan and track paid traffic: channel strategy, creative tests, funnel optimization, scaling and analytics
  • Grow organically: content clusters, repurposing, SEO/GEO audits, brand voice extraction
  • Manage the portfolio: rapid tests, idea tournaments, passive marketplace assets, revenue-phase reviews, daily checks and a lessons library
  • Write state and files: update pipeline state, save assets into the project directory, capture reusable learnings
When to use it
Useful for solo founders or bootstrappers who want an AI assistant to drive a structured, prerequisite-gated launch process rather than ad-hoc advice. Best when you are willing to follow the pipeline order and keep a dedicated project directory for its state and generated assets.
Requirements
Runs locally over stdio, typically via npx with the npm package. Needs Node.js and a project directory holding pipeline-state.json and assets/, set through the LAUNCH_ENGINE_PROJECT_DIR environment variable or a project-dir argument, defaulting to the working directory. The README also states Python 3.10+ for the bundled QA test suite.
Before you install
The utility tools write to your project directory: pipeline state, asset files and a learnings file. Several stages concern real spending, including paid traffic tests and scaling campaigns, and the README says the system pauses for decisions involving real money. Generated copy and research should be reviewed before publishing. The README's package name and environment variable differ from the manifest's, so confirm which package and variable your install actually uses.

Installation

In SourceWeft

  1. Open Launch Engine — Business Execution OS in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Asset Factory

[npm version] [License: MIT] [GitHub stars]

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

bash
npx -y asset-factory-mcp

[Asset Factory Demo]


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

bash
npm install -g asset-factory-mcp

Or run directly without installing:

bash
npx -y asset-factory-mcp

Quick Start

Claude Desktop

Add to your claude_desktop_config.json:

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):

json
{  "mcpServers": {    "asset-factory": {      "command": "npx",      "args": ["-y", "asset-factory-mcp"],      "env": {        "ASSET_FACTORY_PROJECT_DIR": "/path/to/your/project"      }    }  }}

From Source

bash
git clone https://github.com/ZionHopkins/asset-factory-mcp.gitcd asset-factory-mcpnpm installnpm run buildnode 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 simultaneously5. 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 weekly — attribution drift happens. What worked last week may not work next week. Stay on top of the data.

Common Mistakes to Avoid

  • Don't build assets before stress_test passes — a GO verdict means the offer is structurally sound. REVISE or REBUILD means fix the foundation first.
  • Don't skip name_lock — changing the business name after assets are built means rebuilding everything. Lock it early.
  • Don't ignore KILL signals — if rapid test metrics hit kill thresholds, kill it. If validation says KILL, capture the lessons and move on. Sunk cost is not a strategy.
  • Don't publish without qa clearance — unvetted copy with unattributed claims or persona misalignment damages trust and conversion rates.
  • Don't run the full pipeline for every idea — that's what rapid_test is for. Test 5-10 ideas cheaply, then invest the full pipeline in the winner.

Revenue Phase System (New in v1.2.0)

Optional overlay that tracks revenue progression through four phases:

PhaseGoalGate to Advance
SignalGet intent expressedEmail signup, deposit, DM response
CashClose first saleFirst payment received
RepeatClose 3+ at same price3 cumulative sales
ScaleHit target MRRSustained monthly revenue

How to enable: Run portfolio_triage to select active pipelines. Selected pipelines get revenue_phase: "signal". Run revenue_review weekly to track progress.

scout now includes a Sales Cycle Reality Check that estimates days-to-first-sale per market (GREEN <=14d, YELLOW 15-30d, RED >30d). This feeds into the Profit Velocity Score used by portfolio_triage.

Automated QA Test Suite (New in v1.1.0)

The pipeline includes an automated QA test suite that runs at 3 points:

GateWhenWhat It Catches
Pre-DeployBefore deploy generates assetsMissing research, broken unit economics math, placeholder text
Post-DeployAfter assets written, before qaHTML issues, exposed API keys, email subject length, missing CTAs
Post-QAAfter persona correctionsStructural issues introduced by corrections

Test modules in qa-tests/:

  • test_landing_page.py — HTML structure, CTA presence, secret detection
  • test_campaign_assets.py — Email/ad validation, brand consistency
  • test_research_report.py — Section completeness, citation density, contradiction detection
  • test_unit_economics.py — Margin positivity, CAC/LTV ratio, math verification

Requires: Python 3.10+

Listings

Listed on MCP Server Hub | MCP Registry

License

MIT

Source: README.md at commit 1d91652

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.1.0LatestSep 16, 2026

Score

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