What this error means

We encountered an issue when using your API key: Streaming error is a Cursor failure pattern reported for developers trying to fix api key rejected by cursor ide despite being valid elsewhere (works in other apps); need resolution for paid cursor subscription users.. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Verified via GitHub search results (kio-gateway issue #53, 2026-01-23) confirming Cursor IDE rejects valid API keys with 'Streaming error'. Also supported by openai/codex #4092 showing similar auth issues with valid keys. Distinct from 'OpenAI API key not working' in covered-errors.md which refers to invalid keys. Category: Cursor (approved). Strong signal for paid Cursor users who have verified keys.

Common causes

  • Verified via GitHub search results (kio-gateway issue #53, 2026-01-23) confirming Cursor IDE rejects valid API keys with 'Streaming error'. Also supported by openai/codex #4092 showing similar auth issues with valid keys. Distinct from 'OpenAI API key not working' in covered-errors.md which refers to invalid keys. Category: Cursor (approved). Strong signal for paid Cursor users who have verified keys.

Quick fixes

  1. Confirm the exact error signature matches We encountered an issue when using your API key: Streaming error.
  2. Check the Cursor 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.