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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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