What this error means
MCP connector: model intermittently emits tool_use instead of mcp_tool_use for tools declared in mcp_toolset with configs.<tool>.enabled: true is a Anthropic API failure pattern reported for developers trying to fix anthropic mcp connector beta returning wrong content block type (tool_use vs mcp_tool_use) causing tool invocation failures in llm agent tool declarations. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub Issue #1581 in anthropics/anthropic-sdk-python (open, May 21 2026). Under mcp-client-2025-11-20 MCP connector beta, intermittent behavioral regression in content block type emission. Impacts LLM-driven agent workflows using MCP tool protocols. Category: Anthropic API per exact mapping — this is a direct Anthropic SDK/MCP protocol issue.
Common causes
- GitHub Issue #1581 in anthropics/anthropic-sdk-python (open, May 21 2026). Under mcp-client-2025-11-20 MCP connector beta, intermittent behavioral regression in content block type emission. Impacts LLM-driven agent workflows using MCP tool protocols. Category: Anthropic API per exact mapping — this is a direct Anthropic SDK/MCP protocol issue.
Quick fixes
- Confirm the exact error signature matches
MCP connector: model intermittently emits tool_use instead of mcp_tool_use for tools declared in mcp_toolset with configs.<tool>.enabled: true. - 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.