What this error means

SSE stream error returns HTTP 200 instead of actual error code during mid-stream interruption is a Anthropic API failure pattern reported for developers trying to fix incorrect http status returned when anthropic api sse stream breaks mid-response, causing client-side parsing failures. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub Issue #1258 in anthropics/anthropic-sdk-python by sarth6, opened and closed March 31, 2026. When the Anthropic API SSE stream is interrupted mid-stream, the SDK catches the error but returns status_code=200 instead of propagating the actual error code (e.g., 500/529). This makes client-side error handling impossible because the response body contains an error but the HTTP code says success. Category mapping: direct Anthropic SDK/API error. Not in covered-errors.md.

Common causes

  • GitHub Issue #1258 in anthropics/anthropic-sdk-python by sarth6, opened and closed March 31, 2026. When the Anthropic API SSE stream is interrupted mid-stream, the SDK catches the error but returns status_code=200 instead of propagating the actual error code (e.g., 500/529). This makes client-side error handling impossible because the response body contains an error but the HTTP code says success. Category mapping: direct Anthropic SDK/API error. Not in covered-errors.md.

Quick fixes

  1. Confirm the exact error signature matches SSE stream error returns HTTP 200 instead of actual error code during mid-stream interruption.
  2. Check the Anthropic API account, local tool state, and provider configuration involved in the failing workflow.
  3. 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

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. 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.