A
licenseNot graded
qualityD
maintenanceA local MCP server that gives AI coding agents persistent memory and context across sessions.
11 npm
MIT
mcp-taskflow
by CalebGerman
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TDQS
B3/5.0
Scored across 16 tools
Disambiguation3/5
The CRUD-oriented task tools (delete_task, clear_all_tasks, list_tasks, get_task_detail, query_task, update_task, execute_task, verify_task) are reasonably distinct, but the cognitive cluster—reflect_task, analyze_task, plan_task, process_thought, research_mode—overlaps heavily and an agent could easily pick the wrong reasoning tool. list_tasks vs query_task also blur slightly.
Naming Consistency4/5
Strong verb_noun snake_case pattern throughout (reflect_task, plan_task, delete_task, split_tasks, update_task, execute_task, verify_task). Minor deviations: research_mode is noun-style rather than verb-led, and get_task_detail adds a third token, but overall consistency is high.
Tool Count4/5
16 tools is just above the comfortable range but each covers a plausible distinct operation within a task-management workflow. Slightly heavy, with some reasoning tools that could arguably be consolidated.
Completeness4/5
Good lifecycle coverage: task creation (plan_task/split_tasks), read (list_tasks, get_task_detail, query_task), update, delete, execute, and verify are all present, plus project rules and server info. Minor gaps around explicit single-task creation semantics and no dedicated dependency-graph query beyond get_task_detail.
Maintenance
ActivityInactive
ResponsivenessNo issues