Codesearch FAQs

Question 1

How does Codesearch ensure privacy and local processing?

Accepted Answer

Codesearch is designed for complete privacy. All semantic processing, indexing, and searching are performed fully locally on your machine using ONNX models. No data or code snippets ever leave your environment, ensuring your intellectual property remains secure and offline.

Question 2

What makes Codesearch fast and efficient?

Accepted Answer

Codesearch leverages Rust for performance, offering sub-second search times after the initial model load. It features incremental indexing, meaning only changed files are re-indexed, resulting in 10–100x faster updates compared to full rebuilds. It also combines vector similarity with BM25 full-text search and optional neural reranking for high accuracy.

Question 3

How does Codesearch integrate with AI coding agents like OpenCode or Claude Code?

Accepted Answer

Codesearch features an MCP server that provides token-efficient tools for AI coding agents. It enables agents to perform semantic search, find symbol references, and retrieve file chunks, facilitating a 'search → narrow → read' workflow that optimizes token usage for agents like OpenCode and Claude Code.

Question 4

What is Codesearch and what problem does it solve?

Accepted Answer

Codesearch is a Rust-powered tool for fast, local, and private semantic code search. It allows developers to query their codebase using natural language (e.g., "where do we handle authentication?"), understanding the meaning of code rather than just keywords. It solves the problem of efficiently navigating large codebases and integrating advanced search capabilities with AI coding agents.

Question 5

Does Codesearch support natural language queries?

Accepted Answer

Yes, natural language queries are a core feature of Codesearch. You can ask questions like "how do we log errors?" or "find data validation logic" and Codesearch will use semantic understanding to find relevant code snippets within your codebase.

Codesearch

Codesearch

Key Features

Use Cases

Key Features

Use Cases