What this error means
"No OAuth flow is in progress for {provider}. Call mcp__{provider}__authenticate first" is a Claude Code failure pattern reported for developers trying to fix claude code mcp server oauth flow where pkce state is lost between authenticate and complete_authentication steps. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub bug report on claude-code repo: HTTP-type MCP servers with OAuth lose in-memory PKCE state before complete_authentication can consume it. Configured .mcp.json with oauth causes auth flow to fail silently. This blocks all MCP-based integrations (Asana, Datadog, Slack etc.) for enterprise users. Mapping to AI Coding Tools: Claude Code is a paid AI coding IDE, MCP auth is integral to its workflow.
Common causes
- GitHub bug report on claude-code repo: HTTP-type MCP servers with OAuth lose in-memory PKCE state before complete_authentication can consume it. Configured .mcp.json with oauth causes auth flow to fail silently. This blocks all MCP-based integrations (Asana, Datadog, Slack etc.) for enterprise users. Mapping to AI Coding Tools: Claude Code is a paid AI coding IDE, MCP auth is integral to its workflow.
Quick fixes
- Confirm the exact error signature matches
"No OAuth flow is in progress for {provider}. Call mcp__{provider}__authenticate first". - Check the Claude Code account, local tool state, and provider configuration involved in the failing workflow.
- Verify the account session, API key, provider settings, and environment where the failing tool is running.
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.