Code RAG FAQs

Question 1

Which AI development environments does Code RAG integrate with?

Accepted Answer

Code RAG integrates seamlessly via the MCP (Model Context Protocol) with popular AI-assisted development tools such as Claude Code and the Zed editor, enhancing their context awareness.

Question 2

Does Code RAG require external AI APIs for its semantic capabilities?

Accepted Answer

No, Code RAG uses LM Studio for on-device, local embeddings. This means no external API calls are necessary, ensuring data privacy and allowing for offline functionality.

Question 3

How does Code RAG facilitate codebase re-indexing and programmatic access?

Accepted Answer

Code RAG provides an HTTP API that enables automatic re-indexing via Git hooks and offers programmatic access, making it easy to keep your code index up-to-date with your latest changes.

Question 4

What is Code RAG and how does it improve code search?

Accepted Answer

Code RAG is an MCP server for semantic code search that replaces traditional text-based tools. It allows developers to find code by concept and understanding, providing more relevant results than simple keyword matching.

Question 5

What programming languages and file types does Code RAG support?

Accepted Answer

Code RAG offers robust multi-language support, capable of indexing and searching across Go, Python, JavaScript/TypeScript, Terraform, YAML, and other common file types.

Code RAG

Code RAG

Key Features

Use Cases

Key Features

Use Cases