MCP server with UI capabilities using the Apps Extension
Server demonstrates partial tool implementation with mixed quality. Tools have descriptions and basic input schemas, but several lack depth, parameter descriptions are minimal, and output schemas are not documented. The naming is action-oriented (verb_noun pattern), which is good. However, parameter documentation is sparse, error handling is absent, and the playground-style tools lack real-world robustness. STDIO transport limits practical deployment. Tools appear to prioritize UI rendering over functional completeness.
Display an interactive sales database explorer with filtering, sorting, and aggregation capabilities.
Display an interactive feature flag selector UI. Allows browsing and selecting feature flags from different environments.
Display an interactive flame graph visualization for performance profiling. Shows call hierarchy with execution time. Click frames to zoom, analyze hot paths.
Display a Hello World greeting with optional interactive UI
Display an interactive list sorting UI. User can drag to reorder items, save the sorted order, or ask the AI to sort the list.
Parameter descriptions are minimal or missing. The 'profile' parameter in flame_graph says 'Profile data (uses simulated data if not provided)' but does not describe the expected format, structure, or schema. Similarly, 'data' in database_query lacks any guidance on required fields, data types, or constraints.
Output schemas are not documented. The tools return structured content (via structuredContent field) but there is no explicit documentation of what fields, types, or formats are returned. LLMs cannot plan downstream tool chains without knowing what data is available. Example: list_sort returns items and title in structuredContent, but this is implicit, not documented in the tool definition.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 51 | 2025-06-18+ | v2 |
| 2026-03-09 | D | 52 | - | v1 |
No error handling or recovery guidance. Tools have no documented error scenarios, no error classification (retryable vs fatal), and no guidance for LLM recovery. If an invalid flag is passed to feature_flags or malformed data to database_query, there is no specification of what error to expect or how to fix it.
Parameter constraints and formats are not declared. The 'name' parameter in hello_world has no length limit, format, or validation rules documented. The 'items' array in list_sort does not specify minimum/maximum array size. Optional parameters lack guidance on when to omit them vs when they are recommended.
Tool composition and chaining not considered. The five tools are largely independent UI showcases with no documented way to chain results. For example, if database_query returns data, there is no documented mechanism for list_sort to consume that data, or for flame_graph to use filtered results. This limits agent autonomy.