xcodebuildmcp.com: no /llms.txt or .well-known/mcp.json for agents (audit + draft)

Hi — I maintain a handful of published MCP servers and spent this week auditing how well community servers' **websites** serve the agents that discover them (the directories list your server; the site is where an agent actually evaluates it). XcodeBuildMCP scored high on product, and there are a couple of cheap wins:

**Five-point agent-readiness audit of https://www.xcodebuildmcp.com** (run and hand-verified 2026-09-02):

| Check | Result |
|---|---|
| `/llms.txt` | 404 |
| `/.well-known/mcp.json` | 404 |
| MCP HTTP endpoint | no HTTP endpoint at /mcp (stdio via npx) |
| docs `.md` mirrors / `describedby` links | none |
| npm keyword hygiene | keywords include mcp + modelcontextprotocol — hygiene is right |

The pattern this audit keeps finding: the server is listed on directories, but an agent that lands on the site has no machine-readable entry point — `llms.txt` (llmstxt.org v2) plus a `.well-known/mcp.json` twin are the two artifacts agents check first, and Chrome's Lighthouse now audits for one of them.

**Draft `/llms.txt`** — take it as-is or treat it as a starting point:

```markdown
# XcodeBuildMCP
> A Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.

- Repo: https://github.com/getsentry/XcodeBuildMCP
```

If it's useful I'm happy to open a PR with the file(s) instead. And if stdio-only is a deliberate choice, this report's endpoint row is an observation, not a complaint — close with no hard feelings.

*Filed by an automated readiness audit, hand-verified claims. Method + all 10 probe cards: https://gist.github.com/ux-xd/f6408272f9cd643ddd1d698363d2412a*

Locate the website source and deployment configuration in the repository, then review how static files are published. Add the drafted /llms.txt content and a matching /.well-known/mcp.json artifact, and verify both URLs are served successfully with the intended machine-readable information.

Written by the indexing model from the issue text.