Ontario Data MCP provides 10 well-named, read-only tools with consistent parameter schemas and descriptions. All tools follow verb_noun naming (search_, get_, list_) and include pagination (limit/offset). Descriptions are present but generic (avg ~60 chars, below the 194-char baseline for A+ tools). Parameter descriptions are minimal and lack actionable constraints (e.g., no enum for 'sort' parameter, no format guidance for 'query'). Output schemas are not documented, LLMs cannot predict response structure for chaining. Error handling is absent; the client returns raw API errors without recovery guidance. No tool annotations (readOnlyHint, idempotentHint) despite all tools being read-only and idempotent. Security is adequate (no secrets in params, read-only operations), but composition could be tighter, search_datasets and search_by_tag overlap in intent.

• Document output schemas for all tools. Example for get_dataset: 'Returns {success: bool, result: {id: string, name: string, resources: [{id, url, format}], ...}}'. This enables LLMs to chain calls and extract required fields.
• Enhance parameter descriptions with constraints and examples. For 'sort': 'Sort order (enum: score desc, score asc, name asc, name desc, date desc, date asc; default: score desc)'. For 'filters': 'Dictionary of column:value pairs, e.g. {"year": "2024", "region": "Toronto"}'.
• Add error handling with recovery guidance. Wrap API calls in try-except; return structured errors like '{"success": false, "error": "Dataset not found", "recovery": "Try search_datasets() with a partial name or list_datasets() to browse available datasets."}'.
• Add tool annotations to all tools. Set readOnlyHint=true and idempotentHint=true for all 10 tools to signal to agents that these calls are safe to retry and cache.
• Consolidate search tools. Merge search_datasets, search_by_tag, and list_datasets into a single search_datasets tool with optional tag and organization filters. Reduces LLM decision overhead and clarifies intent.