ChunkHound
Facilitates semantic and regex-based search across codebases for AI assistants.
About
ChunkHound offers a powerful search solution for your codebase, enabling AI assistants to intelligently navigate and understand your code. It combines semantic search capabilities, powered by AI embeddings, with robust regex pattern matching. By indexing your project's code chunks using tree-sitter, ChunkHound provides deep context and multi-language support, making your codebase more accessible and searchable for natural language queries and complex pattern discovery within development environments.
Key Features
- Provides rich code context to AI assistants for better understanding
- 2 GitHub stars
- Multi-language support including Python, Java, C#, TypeScript, and JavaScript
- Powerful regex pattern matching for exact code identification
- Local indexing of code chunks for efficient and fast search operations
- Semantic code search using natural language queries
Use Cases
- Developers efficiently locating specific code patterns or functionalities using natural language or regex queries
- Empowering AI assistants like Claude Desktop, Cursor, and VS Code with advanced code search capabilities
- Integrating AI-powered code search directly into existing development workflows and project setups