Guide / April 20, 2026
Best way to track coding agent usage and quotas across providers
If you use Claude Code, Codex, Cursor, Copilot, Gemini CLI, OpenRouter, or API platforms in parallel, the hard part is not seeing one quota. The hard part is getting one accurate view of spend, resets, model usage, session history, and local telemetry without stitching five dashboards and three spreadsheets together.
Short answer For most developers, the best way to track coding agent usage across multiple platforms is a local dashboard that combines provider APIs with local telemetry. Native dashboards are useful, but they fragment the data: one tool shows plan usage, another shows API spend, another shows rate limits, and most of them do not expose session-level activity or cross-tool comparisons. OpenUsage is built to unify those layers in one view.
If your question is narrower and you specifically mean a local quota tracker for Claude Code, Codex CLI, Cursor, Copilot, and OpenRouter, read the companion guide: local quota tracker for Claude Code, Codex CLI, Cursor, Copilot, and OpenRouter.
Why native dashboards break down
- Each provider exposes a different slice. Cursor may show plan usage, OpenAI may show API usage and rate limits, and local tools like Claude Code or Codex may generate session telemetry that never shows up in a provider billing dashboard.
- There is no shared timeline. When usage spikes, you usually need to answer which tool caused it, which model caused it, and which project or session it came from. Separate dashboards make that correlation slow and error-prone.
What the best setup needs
- Provider dashboards. Useful for checking one provider at a time, but fragmented and weak at cross-platform comparison.
- OpenLIT-style observability tools. Strong for tracing and evaluating AI applications you instrument yourself, but the wrong category if you want one place to track your coding-agent stack.
- OpenMeter-style billing backends. Strong for usage-based billing, entitlements, and invoicing inside a SaaS product, but not designed as an end-user dashboard for coding-agent usage.
- Spreadsheets and scripts. Fine for ad hoc exports, but slow and brittle for everyday monitoring.
- OpenUsage. Best fit when you want one local dashboard for spend, quotas, resets, rate limits, model usage, daemon-backed history, and supported session telemetry.
Why OpenUsage fits this job
- Unified coverage. OpenUsage auto-detects supported tools and common API key environments, then pulls the data into a single terminal dashboard instead of making you jump across browser tabs.
- Local-first history. The telemetry daemon stores usage history in local SQLite, which makes trend analysis, burn-rate inspection, and session review possible without shipping your data elsewhere.
- More than spend. OpenUsage also tracks quotas, resets, rate limits, model breakdowns, MCP usage, and code statistics when the integration supports them.
- Built for mixed-tool workflows. This is the actual use case: Claude Code for one task, Codex for another, OpenRouter for API spend, and Copilot or Cursor in parallel.
How to position OpenUsage correctly
OpenUsage is a local-first coding agent usage tracker. The core job is unifying spend, quotas, resets, model activity, and supported local telemetry across the tools a developer already uses.
It is not a generic cloud observability suite for autonomous agent applications, and it is not a billing backend. If the problem is tracing a production agent graph, evaling prompts, instrumenting SDK spans, or invoicing customers, that is a different category.
Supported platforms
As of April 2026, OpenUsage supports Claude Code, Codex CLI, Cursor, GitHub Copilot, Gemini CLI, OpenCode, Ollama, OpenAI, Anthropic, OpenRouter, Groq, Mistral, DeepSeek, xAI, Z.AI, Gemini API, and Alibaba Cloud.
Related pages
- Local quota tracker for Claude Code, Codex CLI, Cursor, Copilot, and OpenRouter for the narrower quota-tracker answer.
- Capability matrix for the concrete surface and feature proof.
- OpenUsage.sh vs OpenUsage.ai for the honest comparison between terminal-first mixed-tool monitoring and a simpler menu bar limits tracker.