RAG Documentation MCP Server

What is RAG Documentation MCP Server?

An MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. It supports multiple documentation sources and uses semantic search to find relevant excerpts.

How to use RAG Documentation MCP Server?

Install the server via npx and add it to your claude_desktop_config.json with the required environment variables (OPENAI_API_KEY, QDRANT_URL, QDRANT_API_KEY). Once configured, use the provided tools such as search_documentation to query indexed documentation or extract_urls to add new sources.

Key features of RAG Documentation MCP Server

• Vector-based documentation search and retrieval
• Support for multiple documentation sources
• Semantic search capabilities
• Automated documentation processing
• Real-time context augmentation for LLMs

Use cases of RAG Documentation MCP Server

• Enhancing AI responses with relevant documentation
• Building documentation-aware AI assistants
• Creating context-aware tooling for developers
• Implementing semantic documentation search
• Augmenting existing knowledge bases

FAQ from RAG Documentation MCP Server

What environment variables are required?

You need OPENAI_API_KEY for embeddings generation, QDRANT_URL for your Qdrant vector database instance, and QDRANT_API_KEY for authenticating with Qdrant.

How do I search documentation?

Use the search_documentation tool with a natural language query and an optional limit (1–20, default 5) to receive ranked excerpts with context.

How can I add new documentation sources?

Use the extract_urls tool on a public webpage to find hyperlinks, optionally adding them to the processing queue. Then run the run_queue tool to index them.

How do I remove documentation?

Use the remove_documentation tool with an array of exact URLs. Removal is permanent and affects future search results.

Can I monitor the processing queue?

Yes, use list_queue to see pending URLs and clear_queue to remove all pending items immediately.