Build monetized APIs in minutes with AI-assisted x402 development

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Building monetized APIs just got faster.

The api-paywall-cookbook repository now includes a CLAUDE.md file that documents every architectural pattern, deployment strategy, and implementation detail used across the cookbook examples. When working with AI coding assistants like Claude Code, this file serves as a knowledge base that helps generate consistent, production-ready code following established patterns.

What's in CLAUDE.md?

The file documents concrete implementation patterns covering multiple frameworks and platforms:

Architectural patterns:

• Factory pattern for platform-agnostic applications
• x402 payment integration flow with middleware
• Multi-network support using CAIP-2 identifiers
• Standard endpoint structure and configuration

Framework support:

• TypeScript with Hono (Node.js, Bun, Cloudflare Workers, Docker)
• Go with Gin
• Python with FastAPI
• Rust with Actix-web

Blockchain networks:

• Solana (devnet and mainnet with USDC addresses)
• Base (Sepolia and mainnet with USDC addresses)
• SKALE (gasless EVM transactions)

Deployment strategies:

• Local development servers
• Multi-stage Docker builds
• Cloudflare Workers via wrangler
• Standalone binaries for Go and Rust

Implementation details:

• Environment variable configuration
• Directory structure requirements
• Usage models (pay-per-request, pay-per-time)
• Testing with the 007 Test Agent

How it works

When you prompt an AI assistant with instructions like "Create a Node.js API that returns weather data and charges $0.01 per request on Solana," the assistant consults CLAUDE.md to understand the required patterns. It then generates code that matches the cookbook standards without you manually reading through examples.

The file provides:

• Complete code references with file paths and line numbers
• Mandatory patterns for consistency across examples
• Environment variable naming conventions
• Required directory structures
• Quality checklists before submission

Example prompts

With CLAUDE.md in your repository, you can use natural language to generate x402-compliant APIs:

"Create a new API that serves jokes and charges $0.001 per request on Solana"

"Add Base network support to the existing weather-api"

"Help me debug why my middleware returns 500 instead of 402"

"Convert the logic-api from Go to Python using FastAPI"

The AI follows documented patterns, ensuring your code integrates correctly with the x402 payment flow.

Why this matters

Traditional payment infrastructure takes weeks to integrate. Credit card processors charge minimum fees that make micropayments impossible. Building payment-gated APIs from scratch requires understanding blockchain protocols, transaction validation, and edge-case handling.

Kobaru removes these barriers. The combination of standardized patterns in CLAUDE.md and working examples across multiple languages means you can build a production-ready monetized API in minutes, not weeks.

This is an "unfair advantage" in the agentic era. While others spend time figuring out payment infrastructure, you ship monetized APIs that AI agents can pay to access. The examples cover Hono, Gin, FastAPI, and Actix across TypeScript, Go, Python, and Rust. The patterns work on Node.js, Bun, Cloudflare Workers, Docker, and standalone binaries.

For manual development

Even without AI tools, CLAUDE.md is a comprehensive reference:

• How the payment flow works end-to-end
• Required directory structures and naming conventions
• Common pitfalls and how to avoid them
• Quality checklist before submitting new examples

The file includes concrete implementation details with actual file paths, USDC token addresses, and network identifiers. Every pattern is backed by production code in the repository.

Try it yourself

The CLAUDE.md file is available at the api-paywall-cookbook repository. Fork it, add it to your project, and start building monetized APIs.

For step-by-step instructions on integrating x402 payments, see the Kobaru documentation.

Welcome to a new revenue generation model for the machine economy.