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title: How We Built MCP Server for Our React Gantt Component
description: SVAR UI Components built an MCP (Model Context Protocol) server to make their React Gantt component documentation AI-accessible. After trying llms.txt (too...
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og:description: SVAR UI Components built an MCP (Model Context Protocol) server to make their React Gantt component documentation AI-accessible. After trying llms.txt (too...
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# How We Built MCP Server for Our React Gantt Component

**[ITNEXT](https://daily.dev/sources/itnext)** · 10 min read · 1 upvotes · 0 comments

## Summary

SVAR UI Components built an MCP (Model Context Protocol) server to make their React Gantt component documentation AI-accessible. After trying llms.txt (too large at 84k tokens) and generic RAG (68% accuracy), they developed a custom context-only architecture that skips redundant LLM processing. Their final approach uses semantic chunking, intent filtering, and returns raw context chunks directly to the agent's LLM for synthesis, achieving 84% accuracy with 11-second average latency. The implementation uses LlamaIndex for RAG and FastMCP for the server layer, with plans to extend support across multiple SVAR components.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://itnext.io/how-we-built-mcp-server-for-our-react-gantt-component-854f895a856f>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#react](https://daily.dev/tags/react), [#llm](https://daily.dev/tags/llm), [#rag](https://daily.dev/tags/rag)

[View this post on daily.dev](https://daily.dev/posts/how-we-built-mcp-server-for-our-react-gantt-component-jol3mddyk)

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