Launch Engine — Business Execution OS

io.github.ZionHopkins由 GitHub 账号 ZionHopkins 发布v1.1.0更新于 Nov 3, 2026

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

发布方自己的服务:Execution Market

概览

AI 生成的概览

本地 stdio MCP 服务器,用 42 个 SOP 工具加 3 个文件写入工具,带独立创业者按阶段走完从点子调研到付费流量验证的创业流程。

可以做什么
  • 运行分阶段商业流程:点子扫描、市场调研、买家画像、方案压力测试与单位经济测算
  • 设计与产出素材:命名、平台与产品架构、销售页、邮件与广告文案,并经过 QA 关卡
  • 规划与跟踪付费流量:渠道策略、创意测试、漏斗优化、放量与数据分析
  • 做自然增长:内容集群、多平台改写、SEO/GEO 审计、品牌语气提取
  • 管理组合:快速测试、多点子批量评估、被动式市场资产、收入阶段复盘、每日检查与经验库
  • 写入状态与文件:更新流程状态、把素材保存到项目目录、记录可复用的经验
适用场景
适合希望让 AI 助手按结构化、有前置条件的流程推进产品上线的独立创业者,而不是零散建议。前提是你愿意按流程顺序执行,并为状态和产出准备一个专用项目目录。
运行要求
以 stdio 本地运行,通常通过 npx 使用 npm 包。需要 Node.js,以及存放 pipeline-state.json 和 assets/ 的项目目录,通过 LAUNCH_ENGINE_PROJECT_DIR 环境变量或项目目录参数指定,默认使用当前工作目录。README 还说明内置 QA 测试套件需要 Python 3.10+。
安装前请注意
工具会写入你的项目目录:流程状态、素材文件和经验库文件。多个阶段涉及真实花费,包括付费流量测试与放量,README 称系统会在涉及真实金钱的决策处暂停。生成的文案与调研内容发布前应人工复核。README 中的包名和环境变量与清单不一致,安装前请确认实际使用的包与变量。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Launch Engine — Business Execution OS,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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

来源:README.md,提交 1d91652

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v1.1.0最新Sep 16, 2026

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其他 Execution 集成