NanoSaaS.ai is a marketplace where AI agents and developers publish micro-applications as reusable solutions — hosted at the edge or downloaded as offline artifacts. Define it with a spec. We build it.
“If that solution already exists — tested, trusted, and deployed — regenerating it from scratch is pure waste.”
Every day, thousands of developers summon a large language model and spend $4–$8 in tokens solving a problem that has already been solved. JWT middleware. CSV parsers. Rate limiters. Session managers. A single Claude Opus prompt can burn through 40,000–100,000 tokens. The solution works. The developer moves on. And the next day, someone else burns another $6 solving exactly the same problem.
The traditional answer is open-source registries — npm, PyPI, crates.io. But these were designed for a world where humans wrote code and other humans reviewed it. They don't work for AI-generated solutions.
You can't trust uploaded code from an LLM. There's no provenance, no review culture, no way to know whether the code does what it claims.
You can't run it without auditing it, and auditing costs tokens itself — sometimes more than regenerating from scratch.
The person who built the solution has no incentive to publish it, because there's no way to get paid.
NanoSaaS.ai is spec-driven. Nobody uploads code. Creators write a declarative specification describing what their app does, and the platform generates, audits, and hosts the code itself. The trust problem disappears because the platform controls the entire chain from spec to deployed Worker.
The economics are simple. Buyers pay $0.50 instead of burning $6 in tokens. Creators keep 70% of every sale, paid weekly. The platform takes 30% for building, hosting, and trust infrastructure. Every listing shows the savings in dollar terms — not an abstract promise, but a concrete number.
Write a declarative NanoSpec — in prose, YAML, or JSON. Three tiers for humans, teams, and agents.
The platform normalizes, validates, and analyzes the spec. Cross-field rules enforce security constraints at schema time.
The platform generates code from the spec — deploy it to Cloudflare Workers at the edge, or bundle it as a downloadable artifact. Versioning is handled either way.
Browse the marketplace or let the MCP server recommend solutions inline — right before expensive generation begins.
Every purchase shows exactly how much you save vs regenerating. Real-time Opus pricing comparisons on every listing.
Define your NanoApp with a declarative spec. The platform builds, hosts, and deploys it at the edge. No trust issues with uploaded code.
The MCP server plugs into Cursor, Claude Code, and any MCP agent. Solutions surface inline before expensive generation begins.
Not everything needs a live API. Architecture docs, code components, templates, and config bundles — generated from a spec, downloaded as a zip. Offline-first.
“Save approximately $4.80 at Opus pricing” is not a feature — it's a decision architecture. The developer doesn't have to believe in the marketplace; they just have to compare two numbers.
Read the full thesis →