Autario MCP presents a well-structured data query tool suite with good naming conventions, clear descriptions, and detailed input schemas. All 4 tools follow verb_noun naming (search_, get_, query_) which aids LLM intent detection. Descriptions are comprehensive (180-380 chars) and include usage guidance. Input schemas are fully specified with types, required fields, and parameter descriptions. However, output schemas are not formally documented, responses are inferred from API behavior rather than declared in the tool definition. Error handling is minimal (tool code shows no specific error recovery guidance for LLMs). Tool composition is sound (each does one thing), though the aggregate query feature in query_dataset borders on scope creep. No security issues detected (no secrets in params, readonly tools). The server lacks progressive complexity features like pagination guidance in descriptions and does not explain when to use list_indicators vs search_datasets.

• Add formal output schema definitions to each tool registration. Example: search_datasets should declare { type: 'object', properties: { datasets: { type: 'array', items: { type: 'object', properties: { dataset_id, title, description, category, publisher, row_count, ontology_fields } } }, total_count, page, limit } }.
• Enhance error handling with recovery hints. Example: 'Dataset not found (ID: {id}). Call search_datasets() to find available datasets.' or 'API rate limit exceeded. Retry in 60 seconds or reduce limit parameter.'
• Explicitly document pagination behavior in search_datasets: 'Returns up to [limit] results (max 100 per page). Use [page] parameter to paginate. Total results may be higher, iterate until results < limit.'
• Clarify aggregation guidance in query_dataset: 'Use aggregate parameter for summary queries (e.g. avg GDP across all years). Omit aggregate and use raw fields for detailed row-level analysis. Aggregations are more token-efficient for single-number answers.'
• Remove the reference to list_indicators in search_datasets description, or add list_indicators as a visible tool with distinct documentation explaining its role vs search_datasets.
• Add an enum or validation note for query_dataset filter operators. Example: 'Operators: eq, neq, gt, lt, gte, lte, like. Column names must match schema from get_dataset_schema().'
• Add toolAnnotations to get_dataset_info, get_dataset_schema, and query_dataset if not already present (readOnlyHint: true, idempotentHint: true for all; destructiveHint: false for all).