Two well-structured tools with complete JSON schemas, clear naming conventions following verb_noun pattern, and excellent parameter documentation. Tool definitions are explicit and verifiable in src/server.ts. However, output schemas are not documented, the response structure is never specified in code or documentation, which violates the pattern:tool requirement. Both tools have good descriptions (180-220 chars), parameter types are properly declared with constraints, and tool annotations (readOnlyHint) are correctly applied. The main gap is the absence of documented return types and output field definitions, which LLMs need to plan downstream tool calls.

• Document the output schema for both tools. Add a TypeScript interface or JSON Schema showing the exact structure returned: e.g., for search_media_files, define { files: Array<{ id: string; filename: string; type: 'image'|'video'|'audio'|'document'; size: number; created: ISO8601; thumbnailUrl?: string }> }. Include this in the tool description or as a separate outputSchema field if the SDK supports it.
• Move authToken and serviceDict to server-side configuration. Accept a user context (user_id or session_token) as a tool parameter instead, and have the server look up the Univex credentials from a secure store. This prevents secrets from appearing in agent logs.
• Enhance error messages with recovery guidance. In univexGet(), catch common HTTP status codes and provide actionable next steps: 401 → 'Authentication failed. Verify your Univex authToken is valid.'; 404 → 'Resource not found. Try a different search query or check if the item still exists.'; 429 → 'Rate limit reached. Please wait a moment and retry.'; 5xx → 'Univex service error. Retry in a few moments.'
• Add structured error handling in the CallToolRequest handler. Wrap tool invocations in try-catch, categorize errors as retryable or user-fixable, and return an error object with a clear message and suggested next action.
• Consider adding pagination control to tool responses. Both tools accept limit and offset parameters, which is good, but the response should include a 'total_count' field so the LLM knows if there are more results. E.g., { files: [...], total_count: 152, returned: 20 }.