📄 中文摘要
构建了一个 MCP 服务器，用于审计 Solana 代币的 rug pull。每次请求调用三个外部 API，并通过 LLM 处理结果，生成风险报告。每次审计的成本约为 0.015 美元。考虑到提供免费服务不可持续，且不想花费数周时间构建计费基础设施，作者采取了简单的付费策略。通过设置 0.02 美元的付费墙，作者能够有效管理成本，同时确保服务的可持续性。该策略在一定程度上缓解了预算压力，并为后续发展提供了可能的方向。
我在我的 AI API 上设置了 0.02 美元的付费墙。我学到了什么
出处: I Put a $0.02 Paywall on My AI API. Here's What I Learned.
发布: 2026年3月10日
📄 English Summary
I Put a $0.02 Paywall on My AI API. Here's What I Learned.
A MCP server was built to audit Solana tokens for rug pulls, calling three external APIs per request and processing results through an LLM to generate risk reports. Each audit costs approximately $0.015. Recognizing that offering the service for free was unsustainable and not wanting to spend weeks building billing infrastructure, the author implemented a simple paywall strategy at $0.02. This approach effectively managed costs while ensuring service sustainability. The strategy alleviated budget pressures to some extent and provided potential directions for future development.