How to connect Trainerize to ChatGPT, Claude and any AI agent

Yes, ChatGPT, Claude and other AI agents can work in your Trainerize account. Cotlet.dev connects your signed-in Trainerize account to AI agents so you can manage clients, programs, check-ins and messages.

What you can ask

List my Trainerize clients who have not been active in the last 7 days and group them by trainer.

Show Alex Rivera's goals, current programs and body stats for the last 90 days.

Find check-ins submitted this week and summarize the answers that need a reply.

List my appointments for next Monday and send Sam Carter a message confirming the time.

Subscribe all clients tagged Challenge to the 6-week Shred master program starting Monday.

Related MCP server: GeniusFitness MCP

Connect in 2 minutes

Get your API key at https://cotlet.dev/app and export it as COTLET_API_KEY.

Claude Code

claude mcp add --transport http cotlet https://cotlet.dev/mcp/v1 --header "Authorization: Bearer $COTLET_API_KEY"

ChatGPT

Settings → Apps → add connector URL https://cotlet.dev/mcp/v1, then sign in with Cotlet.dev. No API key needed.

Cursor

Copy .cursor/mcp.json from this repo into your project:

{
  "mcpServers": {
    "cotlet": {
      "url": "https://cotlet.dev/mcp/v1",
      "headers": {
        "Authorization": "Bearer ${COTLET_API_KEY}"
      }
    }
  }
}

Run it locally (stdio)

This repo is a real MCP server. It speaks MCP over stdio, lists its Trainerize tools without any key, and forwards every tool call to the hosted Cotlet.dev server. The hosted URL above stays the recommended way. Use this when your client only starts local servers.

{"mcpServers":{"trainerize":{"command":"uvx","args":["trainerize-mcp"],"env":{"COTLET_API_KEY":"your-key"}}}}

Or with Docker:

docker build -t trainerize-mcp .
docker run -i --rm -e COTLET_API_KEY trainerize-mcp

Tools: trainerize_guide, trainerize_status, trainerize_open, trainerize_read, trainerize_click, trainerize_type, trainerize_close. Without COTLET_API_KEY a tool call answers: "Set COTLET_API_KEY. Get a key at https://cotlet.dev/app".

Command line

Python 3.10+, nothing else to install. From PyPI:

pip install trainerize-mcp        # or run it once: uvx trainerize-mcp connect
trainerize-mcp connect

Or straight from this repo:

export COTLET_API_KEY="your-key"
python3 trainerize_agent.py connect   # ready config for Claude Code, Cursor, ChatGPT
python3 trainerize_agent.py status    # is Trainerize ready in your Cotlet.dev account
python3 trainerize_agent.py guide     # Trainerize screens and sign-in link
python3 trainerize_agent.py read      # open Trainerize, read the page, close the browser
python3 trainerize_agent.py tools     # list Cotlet.dev tools
python3 trainerize_agent.py serve     # start the stdio MCP server (same as no argument)

Questions from Trainerize users

Does Trainerize have an API?

Trainerize offers API and webhook documentation for some integrations, while Cotlet.dev provides a hosted connection to your signed-in Trainerize account for the client, program, check-in and messaging tools.

How do I connect Trainerize to ChatGPT?

Add Cotlet.dev in ChatGPT with the connector URL https://cotlet.dev/mcp/v1/connect, sign in to Trainerize once in your Cotlet.dev Cloud Browser, and ask ChatGPT in plain words.

Can I use Claude with Trainerize?

Yes. Add https://cotlet.dev/mcp/v1/connect as a custom connector in Claude, or use the Cotlet MCP server from Claude Code, and Claude can work with your Trainerize account.

What can the Trainerize MCP server do?

Cotlet.dev provides 14 Trainerize tools for clients, body stats, check-ins, conversations, programs, appointments, messages, tags and client status in ChatGPT, Claude and other AI agents.

Find it on

• Trainerize on Cotlet.dev

• PyPI package trainerize-mcp

• Odel

• mcpbeat

• Step-by-step guide (PDF) on Internet Archive

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• All apps connected through Cotlet.dev

More: https://cotlet.dev/integrations/trainerize-api-mcp-server?utm_source=github&utm_medium=readme&utm_campaign=trainerize

Start free: https://cotlet.dev/signup?app=trainerize&utm_source=github&utm_medium=readme&utm_campaign=trainerize