The Vectra AI MCP server demonstrates solid definition quality across 26 tools. Strengths include consistent naming patterns (all tools use verb_noun format: list_, get_, create_, delete_), comprehensive parameter schemas with proper JSON Schema types, and detailed descriptions that explain filtering and sorting behavior. However, several notable gaps reduce the score: (1) Output schemas are not explicitly documented in the visible source code, tools return JSON strings but the structure is not formally declared for LLM consumption. (2) No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite the server declaring READ_ONLY and WRITE risk classifications. (3) Error handling guidance is minimal, no recovery hints or per-item success/failure reporting for batch operations. (4) Some parameter descriptions are verbose but lack actionable format constraints (e.g., date strings documented as YYYY-MM-DDTHH:MM:SS but not enforced via pattern fields). (5) Tool descriptions occasionally conflate similar tools (list_detection_ids vs list_detections_with_basic_info vs list_detections_with_details) without clearly explaining when each should be used. Spot-check: get_detection_details has a clear description and proper input schema; list_detections_with_details has comprehensive filtering but no output schema documentation; create_entity_note is a WRITE operation but the description doesn't mention idempotency or retry behavior.

• Add explicit output schema documentation for all tools. Use JSON Schema to declare response structure: e.g., 'Returns an object with fields: {id: integer, name: string, severity: enum(low|medium|high|critical), timestamp: ISO8601_datetime}'. This enables LLMs to extract and chain data correctly.
• Add tool annotations to each tool registration: readOnlyHint=true for all READ_ONLY tools, destructiveHint=true for delete_assignment and mark_detection_fixed(mark_fixed=true), idempotentHint=true for tools where repeated calls are safe.
• Consolidate list_detection_ids, list_detections_with_basic_info, and list_detections_with_details into a single list_detections tool with an optional detail_level parameter (enum: minimal, basic, detailed). Add clear guidance in the description: 'Use detail_level=minimal for ID-only lookups, basic for summaries, detailed for full investigation data.'
• Add recovery guidance to error-prone tools. E.g., for run_investigation: 'If the query syntax is invalid, check the Vectra query documentation at [URL]. Common errors: missing quotes around field values, invalid state enums. Return human-readable syntax errors with the invalid query snippet.'
• Enhance create_entity_note and create_assignment descriptions to state idempotency: 'Creating a note twice with the same entity_id and note text will only create one note (idempotent). Safe to retry on network failure.'
• Add JSON Schema pattern validation to date parameters: start_date/end_date should have pattern: '^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}$' to reject malformed dates at registration time.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry