hey guys, does anyone have a spare claude guest pass? been using chatgpt lately but want to try claude code before subscribing. if anyone has one available, id really appreciate it. thank you

Sharing something I built, plus a few lessons, in case it's useful to others bridging MCP to desktop software.

The problem: TallyPrime is a desktop app with an XML API on localhost:9000. Claude's custom connectors need a public HTTPS MCP endpoint.

The design:

- Claude → remote MCP server (stateless Streamable HTTP, JSON-RPC)

- The server writes each tool call to a command queue in MySQL

- A PowerShell agent on the Tally PC long-polls the server, runs the XML request against Tally and posts the result back

- The server waits for the result and returns it to Claude

Lessons:

- Auth: RFC 9728 protected-resource metadata (path-aware), RFC 8414 discovery, RFC 7591 dynamic client registration, PKCE S256, and refresh-token rotation with reuse detection. Claude's connector flow worked once the 401 carried the right WWW-Authenticate resource_metadata.

- Writes: every write tool returns a preview only. The model has to call a separate confirm tool after the user explicitly approves. Undo works by storing the previous version of each object.

- Shared hosting gotcha: a parent .htaccess denying *.php gave me a 403 that took longer to find than the whole OAuth flow.

Demo video attached. Questions welcome. The product page is https://claudetotally.sysvera.com if you want to see how it's packaged.

At some point endurance training (theory and practice) became just as big a part of my life as professional IT. Recently the two finally overlapped:)

I built an MCP server for Garmin, so now I can just ask Claude “can I go hard today?” and get an answer based on my own HRV, sleep and training load.

and someone can think now..."ok, but it currently exists", however...

building it reminded me of something I keep repeating at work: a good MCP is not a copy of particular API. I wanted tools that answer the questions I actually ask myself before (and after) a workout.

The second thing: AI wrote a fair bit of the code, but it couldn’t tell me what “fatigue” or “readiness” should mean. I had to work that out from my own training experience and sports science, not just take whatever Garmin returns.

so this two points totally refused existing solutions. Everything that existed at the time was merely an API wrapper, completely detached from any domain knowledge regarding endurance training.

so I've built https://endurancetools.github.io/garmin-mcp/ as foundation for basic AI-assisted training

Does it work?
Over the past year my 5K went from 22:36 to 19:32, 10k from 45:00 to 41:40, I finished my first Ironman 70.3, and my ITRA score went from 470 to 590.
To be fair, it’s just an MCP and a long way from the setup I really train with. But that’s where it all starts.

If you run with Garmin, give it a try and let me know what you think.