Analyzes source code across multiple languages to extract structural elements like classes, functions, and parameters using tree-sitter. It provides LLM-optimized markdown output that includes nesting levels, line numbers, and signatures to facilitate codebase navigation.
Enables precise code extraction from 30+ languages using tree-sitter parsing, allowing AI assistants to retrieve functions, classes, and code snippets with accurate line numbers.
Analyzes codebases and extracts all symbols (functions, classes, methods, interfaces, etc.) from 10+ programming languages into LLM-optimized markdown format. Enables AI assistants to understand entire project structures efficiently without processing full source code.
Enables AI assistants to understand and navigate codebases through structural analysis. Provides code mapping, symbol search, and impact analysis using ast-grep for accurate parsing of Python, JavaScript, TypeScript, and Go projects.
Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.
A structural codebase indexer that exposes 18 tools via the Model Context Protocol for AI-assisted code navigation, enabling efficient querying of functions, classes, dependencies, and call chains without reading entire files.
