Server has 12 tools with basic schemas and descriptions, but significant gaps limit production readiness. Descriptions are present but generic (avg ~80 chars, below 194-char baseline). No output schemas documented. Error handling is absent, tools return raw API responses or JSON strings without guidance. Tool naming is verb-forward (search_, get_) which is good, but parameter naming inconsistencies (e.g., 'query' vs 'compound_name') and missing type info on some params reduce clarity. No security considerations visible (credentials, rate limits, input validation). Composition is reasonable, tools are single-purpose, but chaining support is weak (no IDs returned to enable downstream calls).

• Add descriptions to all parameters in tool schemas. Use format: 'The [parameter name] to search for. Valid range: [min-max]. Example: [example].' This matches the 72-char baseline for param annotations.
• Document output schemas for every tool. Specify field names, types, and what each field means. E.g., search_uniprot_entity should document: 'Returns array of {primaryAccession: string, proteinName: string, ...}'.
• Add error handling with recovery guidance. Wrap API calls in try-except; return structured errors like '{error: "User not found", suggestion: "Try search_users() with a partial name"}' instead of raw exceptions.
• Standardize parameter names across similar tools. Use 'query' consistently for search tools; use 'id' or '{resource}_id' for lookups. This reduces LLM confusion and enables better tool chaining.
• Add input validation and constraints. Declare enums for 'db' in search_pdb_entity (already done well); add min/max for 'limit' (e.g., 1-100); add regex patterns for IDs. Document in descriptions.