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Bridge your Claude/OpenAI subs into a team API with per-key cost caps

Hacker News

Bridge your Claude/OpenAI subs into a team API with per-key cost caps

Hey HN, I built this because I wanted to give my team access to Claude and GPT models for internal testing, but the official APIs have no per-key spending controls. You can't cap a key at $5/day or 100 requests/month — it's all or nothing. With non-technical team members in the mix (designers, PMs, QA), one forgotten loop or oversized prompt away from an ugly bill wasn't a risk I wanted to manage manually. Idea was to allow the members to test with these restricted API keys before using official keys. So I built a bridge: it wraps the Claude Code CLI and Codex CLI behind an Express API, backed by existing Max/Pro subscriptions instead of per-token billing. Each team member gets their own API key with hard limits — requests/day, tokens/month, cost caps. Hit the limit and the key stops working. No surprises. An admin dashboard shows who's using what in real time. Key features: - Two providers: /generate (Claude) and /generate-codex (Codex) - Per-user API keys with SHA-256 hashing (shown once, never stored raw) - Per-key hard limits with real-time tracking and enforcement - Admin dashboard for key management, usage monitoring, and request logs - Deploy on a $5 VPS behind Cloudflare Tunnel What it's NOT: A production API replacement. It's for internal tooling and prototyping. CLI invocations add ~3-8s latency vs direct API calls. Important: Wrapping CLI subscriptions behind a shared API may violate the Terms of Service of the underlying providers. Anthropic's Consumer ToS (updated Feb 2026) prohibits using subscription OAuth tokens in third-party tools, and OpenAI's ToS prohibits account sharing. Review the applicable terms before using this. See the Disclaimer section in the README for details. Security was a focus: execFile (no shell injection), timing-safe auth, CSP/HSTS, input validation, rate limiting. Details in SECURITY.md. Stack: Node.js, TypeScript, Express. No database — JSON files on disk. GitHub: https://github.com/Shreyas-Dayal/ai-cli-bridge Would love feedback on the approach and any security concerns I might have missed.

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, user · Missing: mac, agents, macos
96%96% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
29%29% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real time, time tracking · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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