Cqs FAQs

Question 1

What is Cqs and how does it work?

Accepted Answer

Cqs is a powerful tool for semantic code search. It uses local machine learning embeddings (nomic-embed-text-v1.5) and GPU acceleration to understand code by its behavior and functionality, rather than just names. It employs a hybrid search (RRF) to combine semantic similarity with keyword matching for highly accurate results.

Question 2

How does Cqs differ from traditional code search tools like grep?

Accepted Answer

Unlike traditional tools that rely on exact text or name matches, Cqs comprehends what code *does*. This allows you to find functions by concept (e.g., 'retry with exponential backoff') even if you don't know their exact names, making it invaluable for navigating unfamiliar codebases and discovering hidden logic.

Question 3

Does Cqs use AI and is it fast?

Accepted Answer

Yes, Cqs leverages local machine learning for its semantic understanding without sending your code to external services. It's designed for speed, offering GPU acceleration (CUDA support) for significantly faster indexing and querying compared to CPU-only operations.

Question 4

How can Cqs integrate with Claude Code?

Accepted Answer

Cqs can be added as an MCP server to Claude Code, enabling Claude to utilize `cqs_search` for semantic queries. This allows Claude to find code by behavior, navigate projects more intelligently, and discover relevant patterns across your codebase, enhancing its problem-solving capabilities.

Question 5

What programming languages does Cqs support for indexing?

Accepted Answer

Cqs currently provides robust support for semantic indexing and search across several popular programming languages, including Rust, Python, TypeScript, JavaScript, and Go.

Cqs

Cqs

Key Features

Use Cases

Key Features

Use Cases