dev-mcp
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- AlicenseBqualityCmaintenanceProvides AI assistants with persistent memory of your project architecture, development history, and technical decisions, allowing them to give context-aware coding help without needing repeated explanations.1661 npm2MIT
- AlicenseNot gradedqualityFmaintenanceProvides AI coding assistants with persistent project memory by capturing development checkpoints during git commits, branch switches, and inactivity. It enables seamless task resumption through tools that retrieve session history, momentum, and synthesized re-entry briefings.42 npm3MIT
- AlicenseNot gradedqualityBmaintenanceBridges disconnected AI sessions with persistent project memory and automatic session handoff, integrating GitHub workflows for context-aware development.186 npm20MIT
- AlicenseNot gradedqualityCmaintenanceProject management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.9 npm21Apache 2.0
TDQS
Scored across 71 tools
With 71 tools, several serve nearly identical purposes: add_task vs create_task, next_task vs next_best_action, complete_phase vs next_phase, and commit_changes vs git_commit. This overlap creates confusion and makes it difficult for an agent to select the correct tool. Descriptions help somewhat, but the boundaries are fuzzy for many pairs.
Most tools use snake_case with a verb-noun pattern (list_tasks, create_task, get_context), but there are many exceptions like 'doctor', 'blocked_tasks', 'impact_analysis', 'project_dashboard', and 'next_best_action'. The mix of imperative verbs and noun phrases makes it hard to predict tool names, though the majority are still readable.
71 tools is an extreme count for a single MCP server, far exceeding the 3-15 well-scoped range. The massive surface area creates significant cognitive load and makes tool discovery and selection unwieldy for agents.
The tool set covers an impressively broad project lifecycle: file operations, git workflows, task/phase/milestone management, PRD handling, context management, handoffs, dashboards, and architecture validation. Minor gaps exist (e.g., no delete_task or delete_milestone), but core workflows are supported with multiple redundant paths.