
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
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
在 SourceWeft 中
- 打开 控制台中的 Launch Engine — Business Execution OS,将其添加到工作区。
- 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.
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
scoutand 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_testgives 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
Or run directly without installing:
Quick Start
Claude Desktop
Add to your claude_desktop_config.json:
Cursor
Add to your MCP settings (.cursor/mcp.json):
From Source
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
Full Pipeline Flow
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)
Utility Tools (3)
Project Directory Structure
Asset Factory creates and manages files in your project directory:
Configuration
The project directory is resolved in order:
ASSET_FACTORY_PROJECT_DIRenvironment variable--project-dir=CLI argument- Current working directory
First Use
When you run status with no existing pipeline, you'll see:
Three paths available:
- rapid_test — $50-100 paid traffic test in 3-5 days
- scout — Full active pipeline with deep research and validation
- 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_testfirst — don't run the full pipeline on an unvalidated idea. Spend $50-100 to get signal in 3-5 days. If it graduates, then runscout. - 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_intelmeansresearchhas no competitive context. Skippingstress_testmeans 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_checkevery day during validation — it takes 60 seconds and catches problems before they burn budget. - Use
lessonsafter 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_economicswill 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 —
scalerequires 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_analyticsweekly — 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_testpasses — 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
qaclearance — 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_testis 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:
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:
Test modules in qa-tests/:
test_landing_page.py— HTML structure, CTA presence, secret detectiontest_campaign_assets.py— Email/ad validation, brand consistencytest_research_report.py— Section completeness, citation density, contradiction detectiontest_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版本历史
1- v1.1.0最新Sep 16, 2026
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