What this error means
Anthropic APIStatusError with status_code=200 for mid-stream SSE overloaded_error is a Anthropic API failure pattern reported for developers trying to fix anthropic python sdk returning wrong status code 200 for streaming sse errors like overloaded_error. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Filed 2026-03-18, closed. Bug in _streaming.py passing original HTTP response (status 200) to _make_status_error instead of the SSE error's actual status code. Affects all streaming users relying on error classification.
Common causes
- When the Anthropic API streams fine initially but then sends an SSE error event (like overloaded_error/529), the SDK creates APIStatusError with status_code=200 instead of the actual error code. This breaks retry logic, error handling, and monitoring that rely on status codes.
- Filed 2026-03-18, closed. Bug in _streaming.py passing original HTTP response (status 200) to _make_status_error instead of the SSE error's actual status code. Affects all streaming users relying on error classification.
Quick fixes
- Confirm the exact error signature matches
Anthropic APIStatusError with status_code=200 for mid-stream SSE overloaded_error. - Check the Anthropic API account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
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.