courtmesh-mcp
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TDQS
Scored across 12 tools
Each tool has a distinct purpose: get_case vs get_case_analysis clearly separate raw case data from AI analysis; analyze_case vs analyze_consolidated_case distinguish single vs multi-document analysis; search_indian_court_cases vs semantic_search_cases differentiate keyword vs semantic search; request_case_timeline and get_case_timeline form a clear start/poll pair. No two tools are likely to be confused.
Most tools follow a verb_noun pattern with verbs like get, search, analyze, request, check. There is slight inconsistency: 'find_related_cases' could be 'search_related_cases' or 'get_related_cases', and 'request_case_timeline' uses request while its pair uses get. However, the naming is generally predictable and the intent is clear.
12 tools is well within the ideal 3-15 range. Each tool covers a distinct aspect of legal case research (retrieval, analysis, search, timeline, PDF, health), and none feel redundant or unnecessary. The count matches the apparent scope of the server.
The tool surface provides full coverage for the domain: search cases, get case details, read and generate AI analysis (both single and consolidated), find related cases, retrieve PDFs, and fetch timelines. The addition of search_judges and health check round out the workflow. No major gaps are apparent for the stated purpose of accessing Indian court case data and analysis.