A
licenseA
qualityC
maintenanceAn MCP server that turns independent AI agents into a coordinated engineering team with shared task board, context, review loop, and enforced plan-implement-review-iterate workflow.
24
MIT
sprinty
by ebursztein
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TDQS
C2.7/5.0
Scored across 29 tools
Disambiguation4/5
Most tools cleanly separate by resource and action (items, artifacts, subsprints, notes, sprint lifecycle). Item_deprecate's dual role and item_split vs subsprint_new create minor overlap, but descriptions disambiguate them.
Naming Consistency4/5
The dominant pattern is noun_verb (e.g., item_add, artifact_list, subsprint_new, sprint_close), which is consistent and predictable. A few exceptions like info, overview, next, search, changelog, and dashboard_info break the pattern slightly but remain readable.
Tool Count2/5
29 tools exceeds the reasonable threshold for a sprint management server, making the surface feel heavy and harder for an agent to scan. Several tools could be consolidated, such as dashboard_info/dashboard_restart and the numerous item/change resolvers.
Completeness2/5
The toolkit lacks an item_list, missing delete operations for notes and artifacts, and has no subsprint_update. These are significant gaps because agents cannot easily enumerate all items or perform basic lifecycle cleanup, relying instead on indirect routes like subsprint_get or overview.
Maintenance
ActivityMaintained
ResponsivenessNo issues