Author(s): Gergely Szerovay

Originally published on Towards AI.

Connecting Claude Desktop to Your Documentation Through MCP and QdrantImage by the author.

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In the previous article, Getting Better LLM Responses Using AI-Friendly Documentation, we explored how creating AI-friendly documentation can improve the quality of responses from Large Language Models (LLMs). We saw how properly structured Angular documentation helped ChatGPT provide more accurate answers about framework features. Let’s advance our documentation strategy by implementing our own Retrieval-Augmented Generation (RAG) system, powered by Qdrant and designed to work hand-in-hand with Claude Desktop.

Let’s quickly revisit what makes documentation “AI-friendly.” Remember those key principles? Clear headers, comprehensive single files, and focused feature-specific content. These organization techniques aren’t just theoretical — they make a real difference in how LLMs understand our technical docs.

While the file upload approach we explored previously works reasonably well, it comes with limitations. Most notably, you’re constrained by context window sizes, and you need to manually select which documentation to include in each conversation. This creates a frustrating cycle of starting new conversations whenever you need to reference different documentation sections.

Custom RAG systems… Read the full blog for free on Medium.

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Published via Towards AI