As engineering organizations scale, maintaining consistent code quality across hundreds of repositories becomes unmanageable. Traditional CI frameworks distribute governance logic across many repositories, making updates manual, error-prone, and slow.

This technical session presents a new approach: agent-driven autonomous quality enforcement, built using the Model Context Protocol, Kubernetes, and self-hosted LLMs running inside the cluster.

An Agent Service interprets GitHub events, applies enforcement policies, and delegates testing to Context7 which automatically queries a private LLM to generate additional tests. A GitHub MCP server updates the pull request with results and insights, enabling centralized visibility and governance.

This creates a zero-touch developer experience: engineers continue merging code as usual, while the platform autonomously enforces organizational standards, improves software quality, and reduces operational overhead across the entire codebase.