OathScore MCP exhibits significant structural and definitional gaps. While tool names follow verb conventions (get_*, check_*), descriptions lack the depth and specificity needed for robust LLM tool selection. Critical issues: (1) Most tools return JSON-stringified responses (json.dumps) rather than structured objects, forcing LLMs to parse unstructured text. (2) Parameter descriptions are absent or minimal, the `apis` parameter in compare_apis has only 'Comma-separated API names to compare' with no validation constraints, format guidance, or examples of valid API names. (3) Output schemas are completely undocumented, LLMs cannot plan downstream operations or know what fields to extract. (4) Error handling is implicit (via raise_for_status) with no recovery guidance. (5) No pagination support despite tools returning potentially large result sets. (6) No tool annotations (readOnlyHint, etc.) despite all tools being read-only. The server functions as a thin proxy to an external API without the abstraction, validation, or agent-friendly structuring that production tool definitions require.

• Return structured objects from all tools instead of JSON strings. Define explicit TypedDict or Pydantic models for each response (e.g., NowResponse with exchanges: Dict[str, ExchangeStatus], volatility: Dict[str, float], events: EventCountdown). This enables static type checking and gives LLMs a clear schema to plan with.
• Document output schemas in tool descriptions. Example: 'Returns a dict with keys: exchanges (dict of {symbol: {status, next_open, next_close}}), volatility (dict of {vix, vvix, skew}), events (dict of {next_event, today_remaining, week_high_impact})' or use a structured format block.
• Add validation constraints to parameters. For get_score, document valid api_name values as an enum (alphavantage, polygon, finnhub, etc.). For compare_apis, state that apis must be comma-separated, case-insensitive, and each name must be from the valid set. Return a clear error if an invalid name is passed: 'Invalid API: got "foo", valid APIs are: alphavantage, polygon, ...'
• Wrap httpx exceptions in agent-friendly error responses. Example: if BASE_URL is unreachable, return {error: 'OathScore service unavailable. Retry in 30 seconds or contact support.'} instead of an HTTP 500. Categorize errors: 'retryable' (network timeout, 5xx) vs 'user_fixable' (invalid api_name) vs 'fatal' (auth failure).
• Add tool annotations. Use @mcp.tool(annotations=ToolAnnotation(readOnlyHint=True)) on all 8 tools to signal to clients that no state is modified.
• Add limit and offset/cursor parameters to get_now, get_alerts, and compare_apis. Cap results at 100 items and document: 'Returns up to 100 alerts. Use offset to paginate. If more than 100 alerts exist, response includes total_count and next_offset.'