F
licenseNot graded
qualityC
maintenanceEnables orchestrating multi-agent AI coding workflows with Git worktree isolation, parallel testing, and security scanning via the Model Context Protocol.
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Smart Agent Workflow MCP
by vjrivmon
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- AlicenseNot gradedqualityBmaintenanceAutomatically captures project state on git commits, detects context drift, and delivers structured token-budgeted briefings to AI agents, ensuring project continuity without manual effort.52 npm2MIT
- AlicenseNot gradedqualityAmaintenanceEnables any coding model or session to pick up where a previous one left off by keeping handoff state (START / SPEC / DECISIONS / TASKS / LOG) in the repository and projecting each harness's entry files from a single source. It also blocks commits until structural checks and the project's own executable acceptance tests actually pass, providing init, onboarding, session briefing/exit, verification, sync, and task-claim tools.7 npmMIT
- AlicenseBqualityDmaintenanceGives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.198 npmMIT
TDQS
B3.4/5.0
Scored across 20 tools
Disambiguation3/5
Several tools overlap in scope: abort_worktree, rollback_feature, and cleanup_worktree all handle worktree termination at different levels, while create_worktree and start_feature both create worktrees. The descriptions help clarify the hierarchy, but an agent may struggle to choose between low-level and high-level equivalents.
Naming Consistency4/5
Most tools follow a consistent verb_noun snake_case pattern (e.g., start_feature, verify_build, save_context). The exception is 'worktree_status', which is a noun phrase rather than a verb-led command, making it slightly inconsistent with the rest.
Tool Count3/5
At 20 tools, the server is on the heavier side of the typical range. While each tool has a distinct role, some are redundant due to nested operations (e.g., abort_worktree vs. rollback_feature), suggesting the count could be trimmed without losing functionality.
Completeness4/5
The tool surface covers the full feature development lifecycle—start, test, build, merge, rollback, and cleanup—plus memory/context management and documentation. Minor gaps exist, such as no direct way to list completed features or delete specific memories, but these are easily worked around.
Maintenance
ActivityInactive
ResponsivenessNo issues