
TokenWatch
Hey HN! Built this after watching engineering teams repeatedly get surprised by AI API invoices — no visibility into spend until the bill landed. TokenWatch connects to your OpenAI, Anthropic, and Gemini keys and gives you: - Real-time spend dashboard across projects - Budget thresholds with proactive alerts - Anomaly detection for unusual cost spikes - Duplicate call detection (biggest source of wasted spend I've seen) Free tier supports up to 3 AI systems. Built this in ~2 days as a solo project. Happy to answer anything about the build or the problem space.
TokenWatch launched on March 11, 2026 with 3 votes, #3,303 of 23,380 launches that month and more than 50% of that year's launches.
What it does
TokenWatch helps indie developers monitor OpenAI, Anthropic, and Gemini spend in real time, set budget thresholds, detect anomalies, and identify waste from duplicate calls. Connect keys in minutes, get proactive alerts, and stop surprise AI bills before they hit your card.
Track and control your OpenAI, Anthropic, and Gemini API spend in real time. Budget alerts, anomaly detection, and caching insights. Free to start.
Real-time cost monitoring, budget alerts, and caching suggestions for developers building on LLMs. Set up in 5 minutes. Sleep at night. See daily, weekly, and monthly spend trends with real-time provider breakdowns. Receive instant alerts at custom thresholds before your budget gets burned. Track exactly which product features consume tokens and drive spend. Spot unusual spikes in usage with automatic anomaly monitoring. Reveal duplicate calls and high-cost routes to cut waste with smarter caching. Unify OpenAI, Anthropic, and Gemini billing telemetry in one workspace. Securely connect provider API keys and import usage data in minutes. Define daily, weekly, and monthly limits with…from tokenwatch-ten.vercel.app
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AgentWatchJun 2026 · agent-watch.dev · ▲12Hi HN, I’m a solo developer and built AgentWatch to solve a problem I kept running into while building AI agents: preventing runaway loops and unexpected LLM spend before requests reach the model. AgentWatch sits in front of OpenAI, Anthropic, Gemini, Bedrock, Azure OpenAI, Groq, and others to enforce budgets and runtime policies. I’d really appreciate your feedback. If you’re building AI agents, does this solve a problem you’ve experienced? I’d also love to hear what you’d improve or challenge.
- AAAI agents run my one-person company on Gemini's free tier – $0/monthMar 2026 · ▲16
I'm a solo dev in Taiwan. I built 4 AI agents that handle content, sales leads, security scanning, and ops for my tech agency — all on Gemini 2.5 Flash free tier (1,500 req/day). I use ~105. Monthly LLM cost: $0. Architecture: 4 agents on OpenClaw (open source), running on WSL2 at home with 25 systemd timers. What they do every day: - Generate 8 social posts across platforms (quality-gated: generate → self-review → rewrite if score < 7/10) - Engage with community posts and auto-reply to comments (context-aware, max 2 rounds) - Research via RSS + HN API + Jina Reader → feed…



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