Dash MCP augmentation server for project-aware docset recommendations. Analyzes projects, recommends docsets, plans searches, ranks official Dash results, and explains local-vs-official docset coverage.
Enhanced Dash MCP provides 5 tools with complete JSON schemas and descriptions. Most tools follow verb_noun naming conventions and have reasonable parameter documentation. However, several definition gaps prevent a higher score: (1) Output schemas are not explicitly documented, callers must infer return types from descriptions; (2) Error handling descriptions are minimal, tools do not guide recovery steps; (3) No tool annotations (readOnlyHint, destructiveHint, idempotentHint) present despite all tools being READ_ONLY; (4) Parameter descriptions lack constraints (ranges, enums, validation rules); (5) Some descriptions are generic and could be more LLM-optimized. Tool names are clear and action-oriented (analyze_project, list_available_docsets, recommend_docsets, plan_docset_searches, get_docset_coverage), following the verb_noun baseline. Schemas are present and typed for all tools, meeting the 100% baseline for A+ tools in that respect. However, lack of documented output structure and error guidance pushes this to fair (C/D boundary).
Analyze a project directory to detect technologies, frameworks, dependencies, and generate context for docset recommendations.
Analyze and explain which topics are covered in local docsets vs. what would need to come from official Dash or other sources.
List all available local Dash docsets on the system with their metadata, using cached index for performance.
Plan multiple targeted searches across recommended docsets for a given query or topic.
Recommend Dash docsets based on project context (detected languages, frameworks, dependencies).
Output schemas not documented. Tool descriptions mention return data (e.g., 'with their metadata', 'metadata for a Dash cache docset') but do not formalize the response structure. LLMs cannot reliably parse results or plan downstream tool calls without knowing field names, types, and structure.
Error handling lacks recovery guidance. Tools have no documented error cases or suggested next steps. If analyze_project fails on a missing path, or list_available_docsets finds no docsets, what should the LLM do? No guidance is provided.
Tool annotations (readOnlyHint, destructiveHint, idempotentHint) not present. All 5 tools are marked READ_ONLY in metadata but lack explicit tool annotations in the MCP schema. This prevents agents from reasoning about side effects and retry safety without reading descriptions.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 48 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 19 | - | v1 |
Parameter descriptions lack constraint details. E.g., 'max_files' has no min/max bounds; 'match_threshold' says '0.0-1.0' but not whether endpoints are inclusive; 'max_recommendations' default is 10 but no upper bound stated. This invites LLMs to pass invalid values.
Generic parameter descriptions. 'Optional project path for context-aware search planning' (plan_docset_searches) and 'Optional project path for context' (get_docset_coverage) repeat. Descriptions could specify: 'If provided, tool will prioritize docsets matching the project's detected languages and frameworks. If omitted, search planning applies to all available docsets.'