Skip to main content

Docs for AI Agents

These docs are built to be read by AI tools, not just people. If you're using Claude Code, Codex, Cursor, or any assistant that can fetch a URL, you can pull in clean documentation instead of scraping rendered HTML.

Clean Markdown for any page​

Append .md to any documentation URL to get a clean Markdown version of that page:

https://docs.wizchat.com/getting-started/quick-start        ← the page
https://docs.wizchat.com/getting-started/quick-start.md     ← clean Markdown

Point your assistant at the .md URL and it gets the content without navigation, styling, or scripts in the way.

Index of every page — llms.txt​

The llms.txt file is a compact, machine-readable index of the whole documentation set, grouped by section, with a one-line summary and a link to the Markdown for each page. It follows the llmstxt.org standard.

https://docs.wizchat.com/llms.txt

Give this to an agent first so it can find the right pages, then let it fetch the specific .md files it needs.

Full corpus — llms-full.txt​

If you'd rather hand the assistant everything at once, llms-full.txt is the entire documentation set concatenated into a single Markdown file.

https://docs.wizchat.com/llms-full.txt

Best for smaller context windows where a single fetch is simpler than following links.

Ask the assistant on this site​

Every page has an Ask AI button and an Ask a question action that open an assistant with access to these docs — handy when you're reading in the browser rather than working from a terminal.

Connect an AI client (MCP)​

For tools that speak the Model Context Protocol (Claude Code, Cursor, and others), WizChat runs a small docs MCP server so your assistant can search and read these docs directly — no scraping, no guessing URLs.

Endpoint (public, read-only): https://www.wizchat.com/api/docs-mcp

Claude Code

claude mcp add --transport http wizchat-docs https://www.wizchat.com/api/docs-mcp

Cursor — use the Connect to Cursor item in any page's More actions menu for a one-click install, or add an MCP server pointing at the endpoint above.

It exposes two tools:

  • search_docs(query) — find the most relevant documentation pages.
  • fetch_page(path) — read a page's clean Markdown.