Launch Engine

Agentic Business Pipeline OS as an MCP server. Full pipeline from idea to revenue — for solo founders and bootstrappers.

npx -y launch-engine-mcp

Why Launch Engine?

Most MCP servers give you one tool. A GitHub integration. A database query. A Slack bot.

Launch Engine gives you 39 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 launch-engine-mcp

Or run directly without installing:

npx -y launch-engine-mcp

Quick Start

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "launch-engine": {
      "command": "npx",
      "args": ["-y", "launch-engine-mcp"],
      "env": {
        "LAUNCH_ENGINE_PROJECT_DIR": "/path/to/your/project"
      }
    }
  }
}

Cursor

Add to your MCP settings (.cursor/mcp.json):

{
  "mcpServers": {
    "launch-engine": {
      "command": "npx",
      "args": ["-y", "launch-engine-mcp"],
      "env": {
        "LAUNCH_ENGINE_PROJECT_DIR": "/path/to/your/project"
      }
    }
  }
}

From Source

git clone https://github.com/ZionHopkins/launch-engine-mcp.git
cd launch-engine-mcp
npm install
npm run build
node dist/index.js

How It Works

Launch Engine is a two-layer tool system:

Layer A — 39 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

Four 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

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)

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 (39)

| 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) |

Utility Tools (3)

| 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 |

Project Directory Structure

Launch Engine 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
        └── 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. LAUNCH_ENGINE_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.

Automated QA Test Suite (New in v1.1.0)

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

| Gate | When | What It Catches | |------|------|----------------| | Pre-Deploy | Before deploy generates assets | Missing research, broken unit economics math, placeholder text | | Post-Deploy | After assets written, before qa | HTML issues, exposed API keys, email subject length, missing CTAs | | Post-QA | After persona corrections | Structural 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