What this error means
API Error: Server is temporarily limiting requests (not your usage limit) · Rate limited is a Claude Code failure pattern reported for developers trying to fix server-side transient rate limiting that breaks parallel multi-agent workflows and forces manual re-dispatch of threads. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue #60562 on anthropics/claude-code by matisyahu3 (May 19, 2026). Max plan user reports Anthropic-side capacity throttling killing 8-thread parallel Agent dispatches. Error explicitly states 'not your usage limit' — this is platform-side, not account-quota. No auto-retry; users lose AFK work silently. Multiple related issues filed (#53922, #42947, #50841). Category mapped to AI Coding Tools per approved list for Claude Code.
Common causes
- GitHub issue #60562 on anthropics/claude-code by matisyahu3 (May 19, 2026). Max plan user reports Anthropic-side capacity throttling killing 8-thread parallel Agent dispatches. Error explicitly states 'not your usage limit' — this is platform-side, not account-quota. No auto-retry; users lose AFK work silently. Multiple related issues filed (#53922, #42947, #50841). Category mapped to AI Coding Tools per approved list for Claude Code.
Quick fixes
- Confirm the exact error signature matches
API Error: Server is temporarily limiting requests (not your usage limit) · Rate limited. - Check the Claude Code account, local tool state, and provider configuration involved in the failing workflow.
- Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.