Why this server?

This server directly addresses the user's need by scanning codebases to extract structural information (classes, functions, etc.) and outputting it in LLM-friendly formats, which fits the 'fully clean by any LLM model' requirement.

Why this server?

This server is an excellent fit as it analyzes codebases, extracts all symbols (functions, classes, etc.), and outputs them in an 'LLM-optimized markdown format' specifically designed for AI assistants to understand project structures efficiently.

Why this server?

This server is designed to transform code repositories into 'LLM-friendly formats, preserving context and structure,' which directly matches the user's request for discovering codebase structure and generating it for LLMs.

Why this server?

This tool helps LLMs understand and navigate complex codebases by providing 'continuous repository mapping capabilities,' which implies discovering and generating code structure.

Why this server?

This server performs 'structural analysis of functions and classes across multiple programming languages,' directly fulfilling the requirement to discover codebase structure.

Why this server?

This server enables LLMs to understand and analyze code structure through function call graphs, allowing AI assistants to explore relationships and dependencies, which aligns with generating code structure for LLMs.

Why this server?

This server provides tools for 'codebase analysis' and allows LLMs to 'explore project structures,' which covers discovering the codebase and making its structure accessible.

Why this server?

This server 'analyzes codebases and generates contextual prompts' to help AI assistants understand code repositories, implying it extracts structural information in an LLM-consumable format.

Why this server?

While language-specific, this server provides 'semantic understanding of C++ codebases' and helps LLMs 'find classes, functions, and their relationships,' which is a direct match for generating code structure.