Ragdocs FAQs

Question 1

What is Ragdocs?

Accepted Answer

Ragdocs is a tool that allows you to semantically search your documentation using natural language. It stores your documentation in a vector database (Qdrant) and lets you query it as if you were talking to a human expert.

Question 2

What are the requirements for using Ragdocs?

Accepted Answer

You'll need Node.js (16+), Docker (for local Qdrant setup, recommended), and either Ollama (free, local) or an OpenAI API key (paid). See the installation instructions for details.

Question 3

What integrations does Ragdocs offer?

Accepted Answer

Ragdocs integrates seamlessly with Cline, Roo-Code, and Claude Desktop via the Model Context Protocol (MCP), bringing semantic search directly to your coding and AI environments.

Question 4

How does Ragdocs work?

Accepted Answer

Ragdocs uses a vector database (Qdrant) to store embeddings of your documentation. When you ask a question, it converts your query into an embedding and searches for similar embeddings in the database, returning the most relevant documentation.

Question 5

How do I add documentation to Ragdocs?

Accepted Answer

You can add documentation by providing URLs to online documentation or uploading local files. Ragdocs then processes and stores the content in its vector database.

Ragdocs

Ragdocs

주요 기능

사용 사례

주요 기능

사용 사례