Trainer Connect MCP

This official MCP server allows personal trainers to manage their business directly through AI assistants like Claude and ChatGPT. It enables users to register new students, create and edit workout programs with exercise videos, schedule or cancel classes, and manage billing and payment statuses. The server utilizes the same API as the main application, ensuring that all actions performed via the AI are consistent with the app's capabilities and permissions.

Endpoint and access

No sign-in: your client connects and lists tools immediately, with no account or key.

No sign-inEndpoint checked 2026-10-19Operated by Trainer Connect

MCP endpoint (Streamable HTTP)

https://api.trainerconnect.com.br/mcp

Vendor documentation

What you can do with it

Register a new student and set fitness goals
Create a weekly workout program with exercises
Schedule or cancel training sessions
Check for overdue payments or missed workouts

Tools advertised by the last live check:

list_students
get_student
get_schedule
list_payments
create_student
search_exercises
create_workout
schedule_class
list_operations
describe_operation
api_read
api_write
find_trainers
get_trainer

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers a Streamable HTTP server. Use --scope project to write .mcp.json for the repo.

Claude Code configuration

claude mcp add --transport http trainer-connect-mcp https://api.trainerconnect.com.br/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).

Codex configuration

codex mcp add trainer-connect-mcp --url https://api.trainerconnect.com.br/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable trainer-connect-mcp in your MCP settings.

Cursor configuration

{
  "mcpServers": {
    "trainer-connect-mcp": {
      "url": "https://api.trainerconnect.com.br/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure). The type must be streamableHttp for a remote HTTP server.

Cline configuration

{
  "mcpServers": {
    "trainer-connect-mcp": {
      "type": "streamableHttp",
      "url": "https://api.trainerconnect.com.br/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start trainer-connect-mcp and inspect its tools.

VS Code configuration

{
  "servers": {
    "trainer-connect-mcp": {
      "type": "http",
      "url": "https://api.trainerconnect.com.br/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.

Gemini CLI configuration

gemini mcp add --transport http trainer-connect-mcp https://api.trainerconnect.com.br/mcp

Claude Desktop

Merge this into claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\), then restart Claude Desktop.

Claude Desktop configuration

{
  "mcpServers": {
    "trainer-connect-mcp": {
      "url": "https://api.trainerconnect.com.br/mcp"
    }
  }
}

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.

Windsurf configuration

{
  "mcpServers": {
    "trainer-connect-mcp": {
      "serverUrl": "https://api.trainerconnect.com.br/mcp"
    }
  }
}

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