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helixui

Using llms.txt with AI tools

There are two ways to give an AI tool helixui: the MCP server (best — live tools) and the static llms.txt endpoints (works with any tool that can fetch a URL).

Fastest path: the MCP server

If your tool speaks the Model Context Protocol (Claude Code, Cursor, Claude Desktop, Windsurf…), connect the helixui MCP server. It exposes live tools — helixui.search, helixui.validate, helixui.fix_jsx, helixui.express_dna — and the manifests as resources, all backed by the same artifacts below.

Terminal window
# Claude Code
claude mcp add helixui -- npx -y @helixui/mcp


# Anything else: run it directly over stdio
npx -y @helixui/mcp
// or add to your mcp.json / client config
{
  "mcpServers": {
    "helixui": { "command": "npx", "args": ["-y", "@helixui/mcp"] }
  }
}

Static endpoints

helixui publishes static endpoints with every build, discoverable via robots.txt, sitemap.xml, a <link rel="llms-txt"> tag, and an HTTP Link: header:

  • /llms.txt — a compact index of every doc page and every component with one-line descriptions. Carries a provenance line (schema, build id, date).
  • /llms-full.txt — the full body of every doc page concatenated, plus the tokens manifest as JSON.
  • /components/<name>.md — one prompt-ready file per component.
  • /tokens-manifest.json, /components-manifest.json — machine-readable, each stamped with a $meta / schema provenance block so a client can cache-validate (ETag + If-None-Match 304s are supported).

With Claude Code

Add helixui as a documentation source the agent can fetch:

Terminal window
# in your project
echo "Read https://your-helixui-host/llms.txt before suggesting any helixui component or token." >> CLAUDE.md

For deeper context, swap in llms-full.txt. It is large but covers the whole system in one fetch.

With Cursor

Settings → Features → Docs → Add new doc → paste the URL of llms-full.txt. Cursor will index it and use it for completions.

What’s in llms-full.txt

  1. A short header that tells the model what helixui is.
  2. The full content of every page in apps/docs/src/content/docs/.
  3. Every component’s spec.md (frontmatter + body), so the model sees props, accessibility notes, and example code together.
  4. The tokens manifest.json, embedded as a fenced JSON block.