Markdown RAG FAQs

Question 1

What types of content can I index with Markdown RAG?

Accepted Answer

It's designed to index diverse Markdown documents, making it ideal for personal notes, project documentation, research papers, and any other Markdown-formatted content.

Question 2

How does Markdown RAG protect my data privacy?

Accepted Answer

It operates entirely locally, ensuring that your sensitive Markdown documents and their indexed data never leave your system, providing full data privacy and control.

Question 3

Is an external database required to use Markdown RAG?

Accepted Answer

No, Markdown RAG includes an integrated, self-contained vector database, eliminating the need for external database setup and simplifying deployment.

Question 4

What is Markdown RAG and what does it do?

Accepted Answer

Markdown RAG is a local-first, command-line tool that indexes and allows semantic search across your Markdown documents using vector embeddings and a built-in vector database.

Question 5

What makes its search 'semantic'?

Accepted Answer

Instead of just keyword matching, Markdown RAG uses vector embeddings to understand the meaning and context of your content, allowing you to find relevant information even if exact keywords aren't present.

Markdown RAG

Key Features

Use Cases

Markdown RAG

Key Features

Use Cases