为开发者提供实时AI模型价格查询与变更通知的API服务
原始条目：Show HN: Indextkn – live list prices for 900 AI models in one API
开发者在构建LLM应用时，难以获取和比较不同模型提供商的实时价格，手动维护数据易过时且耗时，影响成本优化决策。
使用LLM的独立开发者、初创公司技术负责人，聚集于GitHub、Hacker News、Reddit的r/artificial及r/MachineLearning、技术博客评论区。
AI模型数量激增，价格频繁变动，开发者对成本敏感，但缺乏统一数据源，市场存在空白。
提供实时、多提供商覆盖、带置信度验证的价格数据，并通过API、Webhook、MCP多种接入方式，简化集成。
采用订阅制，提供免费层（有限请求），付费层$29-$99/月，按请求量和高级功能分级。
后端用Node.js或Python（FastAPI），数据库用PostgreSQL，部署用Vercel或AWS，爬虫用Playwright，AI辅助编码和测试。
I've been building quite a few POCs that use LLMs at work, and something that always comes up is: "OK, how much are we paying for X?" Or the one that follows right after: "If we use another model, would that be cheaper?" So far, what we've used are hardcoded files or keeping the data in our DB. This won't hold when moving to prod. It also keeps us very limited when it comes to creating price comparisons across different models/providers. indextkn came from that. Over the past 3 weeks, I've spent a lot of time understanding more about pricing, when prices usually change, discounts (flex, batch, based on X number of tokens, etc.)... and it's massive. The current state is not where I want it to be. The goal is to cover all prices and modalities offered by all providers. But right now, we have: 1. Prices fetched every couple of minutes, served via API, MCP, or you can install our SKILL. 2. Webhooks per model + provider, so you get a notification when anything changes. Most of the time went into the logic to get the prices right and the logic to validate them! We have different levels of confidence, and I'm particularly proud of how we're double-checking when a price seems off (a combin