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12 changes: 6 additions & 6 deletions docs/guides/mcp-server.md
Original file line number Diff line number Diff line change
Expand Up @@ -39,13 +39,13 @@ The MCP server indexes the full DHTMLX Suite documentation across all components

The DHTMLX MCP server uses a Retrieval-Augmented Generation (RAG) pipeline combined with the Model Context Protocol (MCP) to provide AI assistants with up-to-date documentation. Before any of that, the assistant first figures out which part of a request actually needs a documentation lookup and handles the rest from its own knowledge.

At a high level:
Here's what that looks like for the prompt *"I want to create a layout with a calendar in one cell, and a grid in another,"* one example among the many Suite components this same mechanism covers:

1. The assistant sends the part of the query that needs documentation through MCP.
2. The server determines which product documentation is relevant.
3. Documentation content is retrieved from a vector index.
4. The retrieved context is sent back to the assistant.
5. The assistant combines that context with the part of the request it already handled on its own to generate a response.
1. The assistant sends the query through MCP.
2. The server determines that it touches the Layout, Calendar, and Grid documentation.
3. Since the answer requires generated code, the server routes the query to *Search*, one of two workflows; a narrower factual question would route to *Inference* instead, which reads the same pages and answers directly.
4. *Search* retrieves the matching pages from a vector index built on the current documentation and sends them back to the assistant as context.
5. The assistant configures the layout, calendar, and grid together using that context.

This approach allows AI tools to generate answers based on current documentation.

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