An MCP server that enforces hard quality gates on AI coding agents, including forced web search, planning, and empirical test execution, to prevent common failure modes and ensure production-grade code.
An MCP server that implements the Contract-First Agentic Workflow (CFAW) methodology for AI-assisted software engineering, using a Mixture-of-Agents architecture with six tools to enforce contract-first development and maintain architectural integrity across coding sessions.
An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.
An MCP server that turns independent AI agents into a coordinated engineering team with shared task board, context, review loop, and enforced plan-implement-review-iterate workflow.
Transforms 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.