What this error means

MCP per-server timeout not enforced on individual tool calls (stdio hangs indefinitely) is a Claude Code failure pattern reported for developers trying to developer using claude code with custom mcp tools experiences infinite hangs because server-level timeouts don't apply to individual tool invocations. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue #53641 (anthropics/claude-code) — recently closed (completed) May 24, labels: area:mcp, bug, has repro. While resolved, the error pattern ('stdio hangs indefinitely') represents a significant UX blocker for teams using custom MCP servers. Distinct from general timeout/rate-limit topics. Good for capturing users searching before fix ships.

Common causes

  • GitHub issue #53641 (anthropics/claude-code) — recently closed (completed) May 24, labels: area:mcp, bug, has repro. While resolved, the error pattern ('stdio hangs indefinitely') represents a significant UX blocker for teams using custom MCP servers. Distinct from general timeout/rate-limit topics. Good for capturing users searching before fix ships.

Quick fixes

  1. Confirm the exact error signature matches MCP per-server timeout not enforced on individual tool calls (stdio hangs indefinitely).
  2. Check the Claude Code 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.