Tree-sitter
Analyzes code using tree-sitter to provide context-aware code understanding for AI assistants.
About
This tool serves as a Model Context Protocol (MCP) server, leveraging tree-sitter to empower AI assistants like Claude with intelligent access to codebases. It provides code analysis capabilities, offering flexible code exploration at various levels of granularity while ensuring appropriate context management to avoid overwhelming the AI's context window. By utilizing Abstract Syntax Trees (ASTs), the server enables structure-aware code understanding, efficient traversal, and powerful search capabilities through text and tree-sitter queries. Features like caching, symbol extraction, and dependency analysis enhance performance and provide valuable insights into code relationships.
Key Features
- Enables structure-aware code understanding using ASTs
- Caches parse trees for optimized performance
- Offers powerful code search capabilities
- Supports many programming languages via tree-sitter
- Provides context management for AI assistants
Use Cases
- Enabling context-aware code search and exploration
- Enhancing code understanding for AI assistants like Claude
- Performing code analysis tasks such as symbol extraction and dependency analysis