ChunkHound FAQs

Question 1

What kind of search capabilities does ChunkHound offer?

Accepted Answer

It offers both semantic search, allowing natural language queries like 'Find database connection code', and powerful regex search for exact pattern matching across your files.

Question 2

Which programming languages does ChunkHound support?

Accepted Answer

ChunkHound supports a wide range of languages including Python, Java, C#, TypeScript, JavaScript, and Markdown, extracting key structural elements for efficient search.

Question 3

What is ChunkHound and how does it help developers?

Accepted Answer

ChunkHound is a tool that enables AI assistants to perform intelligent searches across your codebase using natural language (semantic) or precise regex patterns. It provides rich code context, helping AI assistants better understand and interact with your projects.

Question 4

Is an OpenAI API key required to use ChunkHound?

Accepted Answer

An OpenAI API key is necessary for ChunkHound's semantic search features, as it relies on OpenAI embeddings. However, regex-based searching functions perfectly without an API key.

Question 5

How does ChunkHound integrate with AI assistants and IDEs?

Accepted Answer

ChunkHound uses the MCP protocol to integrate seamlessly with AI assistants and editors like Claude Desktop, VS Code, and Cursor, allowing them to leverage its code search capabilities directly within your workflow.

ChunkHound

ChunkHound

Key Features

Use Cases

Key Features

Use Cases