Ship Your Product Documentation Into Customer's Chat Client

The article proposes embedding product documentation directly into an MCP (Model Context Protocol) server to prevent LLM hallucination when customers ask AI assistants about vendor products. Instead of maintaining a RAG pipeline with vector databases and embeddings, documentation is preprocessed into a navigable index at release time and compiled into the server binary. At runtime, the LLM browses this index to locate relevant sections and retrieves authoritative, intact content without any external calls.