Server has 8 well-named tools with clear verb-noun patterns (discover_, get_, etc.). All tools have descriptions (10 - 200 chars, within baseline 194 avg). Input schemas are present and use Zod with type declarations. However, output schemas are NOT documented, responses are JSON.stringify'd without explicit field definitions. Parameter descriptions are present but some lack format/constraint details (e.g., 'dimension_filters' object lacks structure docs). Error handling returns isError flag but lacks recovery guidance. No tool annotations (readOnlyHint, destructiveHint). Overall: solid foundation, but missing output documentation and error guidance expected of production tools.

• Document output schemas for all tools. Define return object fields, types, and examples. E.g., discover_dataflows returns {count: number, dataflows: [{id: string, name_it: string, name_en: string, description_it: string, description_en: string, id_datastructure: string}]}.
• Enhance error messages with recovery guidance. E.g., 'Dataflow not found: 101_1015_DF_DCSP_COLTIVAZIONI_1. Try discover_dataflows() with keywords to find available dataflows.' or 'Invalid dimension_filters: expected object with dimension names as keys (e.g., {"AGRI_MADRE": "100,200"}).'
• Add tool annotations. Mark all tools with readOnlyHint=true (all are read-only). This signals to agents that retries are safe and no side effects occur.
• Document dimension_filters structure in get_data. Provide example: {"AGRI_MADRE": "100,200", "FREQ": "A"} and explain that keys are dimension names from get_constraints output.
• Add pagination to discover_dataflows. Accept optional limit (default 20, max 100) and offset parameters. Return total count and next_offset in response to enable iteration over large result sets.