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 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 turns independent AI agents into a coordinated engineering team with shared task board, context, review loop, and enforced plan-implement-review-iterate workflow.
MCP server that keeps AI agents from over-engineering by providing decision ladders, diff scoring, and prune reviews. It helps enforce minimal-code discipline through CLI, SDKs, and MCP tools.
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
