Local Model Suitability MCP

Local Model Suitability MCP is an MCP server that exposes an AI-powered tool to assess whether a local language model is appropriate for a specific task, weighing factors like cost, privacy, latency, and quality. It is designed for developers, AI platform operators, and agent builders who need to programmatically decide if they should use a local model (e.g., Ollama, LM Studio) or fall back to a cloud LLM, based on task requirements and constraints. It integrates with MCP-compatible clients and can be used with Claude, Cursor, Windsurf, and similar agent platforms.