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      <title>How I built a hard budget-cap proxy to stop runaway LLM API bills</title>
      <dc:creator>Aliyu Nazeer</dc:creator>
      <pubDate>Thu, 17 Sep 2026 17:08:07 +0000</pubDate>
      <link>https://dev.to/aliyunazeer07/how-i-built-a-hard-budget-cap-proxy-to-stop-runaway-llm-api-bills-4gil</link>
      <guid>https://dev.to/aliyunazeer07/how-i-built-a-hard-budget-cap-proxy-to-stop-runaway-llm-api-bills-4gil</guid>
      <description>&lt;p&gt;Hey everyone. If you've ever built scripts or side projects using LLM APIs, you probably know the low-key anxiety of accidentally getting stuck in a loop and waking up to an insane cloud bill.&lt;br&gt;
​Big enterprise tools for managing this are usually way too bloated for a solo dev. I just wanted something simple and self-hosted that actually works. So, I built CloudGrip.&lt;br&gt;
​Basically, it’s a lightweight proxy gateway built with Node.js and Express that sits between your code and the LLM provider. It tracks your token usage in real time using Supabase, and it has a hard budget circuit breaker. The moment your spend hits your set limit, it cuts off execution so you don't leak money. I've also wired up a live Paystack subscription flow for it.&lt;br&gt;
​If you want to check it out or test it out, the live project is here: &lt;a href="https://cloudgrip-ai.onrender.com" rel="noopener noreferrer"&gt;https://cloudgrip-ai.onrender.com&lt;/a&gt;&lt;br&gt;
​How do you guys usually handle API budget safety when building AI tools? Would love to hear how other devs manage it&lt;/p&gt;

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