Massu: Governance Layer for AI Coding Assistants with 51 MCP Tools

Massu presents a governance framework designed to manage and control AI coding assistants at scale. By integrating 51 Model Context Protocol (MCP) tools, it enables developers to deploy local and self-hosted coding agents with fine-grained permission controls and monitoring capabilities.

For local LLM practitioners, this is significant because it bridges the gap between running powerful coding models on-device and maintaining organizational safety standards. The MCP standard allows local models to interact with external tools in a standardized way, making it easier to build reliable, governed AI agent systems that don't require cloud API calls.

This type of infrastructure is essential for enterprises and teams looking to adopt local LLMs for development workflows while maintaining security, auditability, and control over model behavior and resource usage.

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Source: Hacker News · Relevance: 8/10