This server has 4 tools with mixed quality. All tools have names starting with action verbs (get_, export_), which is correct. Descriptions are present for all tools and most are reasonable length (72-234 chars). However, parameter schemas show inconsistent depth: some parameters lack descriptions entirely (e.g., 'parallel' in export_weekly_csv has description but 'format' enum values are not individually described), and output schemas are completely undocumented, the tool definitions do not state what fields are returned or their types. Error handling is minimal, no recovery guidance, no actionable error messages visible in the source. The code visible in mcp_server.py only shows imports and helper functions; the actual tool registration is cut off mid-function at @app.list_tools(). This means I cannot fully assess tool registration completeness, which caps overall confidence. Based on visible parameter schemas in the tool definitions provided, schemas are partially defined (type object, properties, required fields present) but lack response documentation entirely.

• Add explicit output schema documentation to all tools. For get_daily_report, document: returns array of objects with fields {task, hours, date, project?} and types. For export_weekly_csv, document the CSV/JSON structure returned.
• Add error handling section to each tool description: 'If date format is invalid, will return error. Use YYYY-MM-DD format (e.g., 2025-01-15).' This helps LLMs self-correct.
• For export_today_csv, either add required parameters (e.g., user_id) or document that it returns the authenticated user's data from the Time Doctor session.
• Fix 'parallel' parameter: change enum to ['auto', 'enabled', 'disabled'] with actual string semantics, or use a boolean type with description 'true=parallel scraping (faster), false=sequential (slower).'
• Add 'Dependencies' section to descriptions: 'Requires Time Doctor login credentials (TD_EMAIL, TD_PASSWORD) to be configured in environment.' This prevents silent auth failures.
• Document rate limits and pagination: if tools can return large datasets, state limits (e.g., 'Returns up to 100 entries; use date ranges to paginate.') and expected response size.
• Add structured error examples to descriptions: 'Invalid date returns: {error: "Date must be YYYY-MM-DD", got: "01-15-2025"}' so LLMs know the error format.
• Ensure tool source code in mcp_server.py includes full tool registration with complete schemas and validation logic visible for audit.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry