What this error means
Datadog MCP OAuth fails with invalid_scope error (works in Claude Code with identical config) is a Claude Code failure pattern reported for developers trying to fix mcp server oauth authentication failures where valid configs work in claude code client but fail on specific third-party mcp servers (e.g., datadog invalid_scope). Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Factory-AI/factory GitHub Issue #1086 (created 2026-05-05) reports Datadog auth failing with invalid_scope error specifically for MCP OAuth flow, even with identical config that works in Claude Code native integration. mapbox/mcp-devkit-server Issue #114 (created 2026-05-15) reports inability to authenticate hosted endpoint via Claude Code. Multiple MCP OAuth integration issues being reported across repos. Category: AI Coding Tools per mapping rules. High growth area as more teams adopt MCP.
Common causes
- Factory-AI/factory GitHub Issue #1086 (created 2026-05-05) reports Datadog auth failing with invalid_scope error specifically for MCP OAuth flow, even with identical config that works in Claude Code native integration. mapbox/mcp-devkit-server Issue #114 (created 2026-05-15) reports inability to authenticate hosted endpoint via Claude Code. Multiple MCP OAuth integration issues being reported across repos. Category: AI Coding Tools per mapping rules. High growth area as more teams adopt MCP.
Quick fixes
- Confirm the exact error signature matches
Datadog MCP OAuth fails with invalid_scope error (works in Claude Code with identical config). - 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.