A
licenseNot graded
qualityC
maintenanceEnables natural language time tracking through AI assistants, integrating with Azure DevOps to log, view, and report work hours without context switching.
41 npm
MIT
WBSO MCP Server
by rubenmaas
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TDQS
B3.2/5.0
Scored across 8 tools
Disambiguation2/5
The tools analyze_wbso_relevance, classify_work, and check_commit_wbso all serve to determine whether work qualifies as WBSO and how to categorize it, creating significant overlap. While descriptions differ slightly (relevance check, classification, commit-specific check), an agent could easily misselect among them.
Naming Consistency4/5
All tool names follow a snake_case verb_noun pattern (analyze_, classify_, check_, get_, log_), which is consistent. Minor inconsistency exists in whether 'wbso' appears in the noun part (analyze_wbso_relevance, get_wbso_criteria vs. classify_work, log_time), but overall the pattern is clear and predictable.
Tool Count5/5
With 8 tools, the server is well-scoped for WBSO management, covering analysis, classification, logging, and status retrieval without unnecessary redundancy. The number feels appropriate for the domain and each tool appears to contribute to the workflow.
Completeness4/5
The tool set covers the core WBSO workflow: checking relevance, classifying work, logging research/development/time, and viewing criteria/status. Minor gaps exist—such as no update or delete operations for logged entries—but for the apparent purpose of documentation and tracking, the surface is reasonably complete.
Maintenance
ActivityInactive
ResponsivenessUnresponsive