A
licenseNot graded
qualityD
maintenanceTransforms AI agents into spec-driven product engineers by managing the software project lifecycle through requirements, design, implementation, and archiving phases with state-aware MCP tools.
23 npm
MIT
multi-agent-mcp
by venkata210
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TDQS
B3.2/5.0
Scored across 13 tools
Disambiguation4/5
Most tools target distinct roles and phases, but review_code and suggest_improvements both analyze code for quality, and analyze_codebase overlaps with review activities. The boundaries are clear enough that agents can select correctly with minor caution.
Naming Consistency4/5
Strong verb_noun pattern for most tools (plan_feature, design_architecture, implement_code, etc.), but collaborate is just a verb and full_workflow uses an adjective_noun form. The outliers are readable and not confusing, just less consistent.
Tool Count5/5
13 tools is well-scoped for a multi-agent development workflow covering planning, architecture, implementation, review, testing, estimation, collaboration, and session management. Each tool clearly earns its place.
Completeness4/5
The surface covers the core development lifecycle end-to-end, including a full_workflow orchestrator and session history management. Minor gaps exist around explicit session creation or non-destructive session deletion, but agents can work around them.