I built an autonomous AI business crew that researches, builds, and publishes AI agent products without human intervention. Here's how it works and what it's produced so far.
The Problem
AI agents need tools to be useful. But most tooling is built by humans for humans, published on human-facing marketplaces.
AI agents can't use Gumroad. They need pip install, uvx, and API keys. So I built a crew that publishes where AI agents actually shop.
The Architecture
The crew runs in cycles, each producing a new product:
Phase 1: Research
Scans GitHub trending, HuggingFace downloads, and community pain points to identify what AI agents need right now.
Phase 2: Build
Generates a production-ready product with code, docs, and metadata for multi-channel publishing.
Phase 3: Publish
Ships to every relevant channel simultaneously: GitHub, PyPI, HuggingFace, Gumroad, and MCP registries.
Phase 4: Repeat
The cycle runs autonomously every 6 hours.
What's Been Built (5 Products)
MCP Servers — install with uvx
| Server | Command |
|---|---|
| Web Search | uvx crewai-web-search-mcp |
| Code Review | uvx code-review-automation |
| Document Intelligence | uvx document-intelligence-server |
CrewAI Skills — install with pip
| Pack | Command |
|---|---|
| Browser Automation | pip install crewai-browser-automation-skills-pack |
| Enterprise Integration | pip install crewai-enterprise-integration-skills-pack |
The Business Model
Each MCP server includes a built-in billing backend:
- Free: 50 calls/day — no key needed
- Starter: $20 for 2,000 calls
- Pro: $100 for 12,000 calls
Credits work across all servers. The billing API is open source.
Early Results (24 hours)
- 5 products on PyPI, GitHub, and HuggingFace
- 9 Gumroad listings
- 37 GitHub repo views from organic discovery
- $0 revenue (launched yesterday)
What's Next
The crew runs every 6 hours, producing ~4 products per day. Upcoming: data enrichment MCP server, social media intelligence, knowledge graph MCP server.
GitHub Showcase: https://github.com/KennyWayn3/crewai-mcp-servers
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