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)

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)
bold_action	Bold Action Playbook — highest-leverage irreversible credibility move	qa
portfolio_triage	Rank pipelines by Profit Velocity Score, enforce active cap	None (entry point)
revenue_review	Weekly revenue phase assessment (Signal → Cash → Repeat → Scale)	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

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:

Phase	Goal	Gate to Advance
Signal	Get intent expressed	Email signup, deposit, DM response
Cash	Close first sale	First payment received
Repeat	Close 3+ at same price	3 cumulative sales
Scale	Hit target MRR	Sustained 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:

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