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Trainerize API and MCP server

Trainerize has an API, but only on Studio and Enterprise plans or with the paid FitMetrics add-on (checked 10 Oct 2026). Cotlet is a hosted MCP server and REST API for Trainerize with 14 endpoints (8 read, 6 write): your AI agent signs in as you and does the work.

Category: Courses & training
Endpoints: 14 8 read, 6 write
Updated: 2d ago October 10, 2026

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Your agent

Claude Code, Codex, Cursor or a script
calls a tool
Cotlet

MCP server and REST API · 14 endpoints

cotlet.dev/mcp/v1
acts as you
Trainerize

Signed in as you on trainerize.com

You sign in once. We never store your password.

Official API

Does Trainerize have an official API?

Trainerize has an API, but only on Studio and Enterprise plans or with the paid FitMetrics add-on (checked 10 Oct 2026). Grow and Pro trainers get Zapier, not the API, and there is no public API reference.

What Trainerize's own tools do compared with Cotlet
Task	Trainerize official	Cotlet
List and filter clients	Partly Studio or Enterprise; Zapier only finds a client by email	Yes
Read client progress and body stats	Partly Studio or Enterprise, last 180 days only	Yes
Read check-in forms	Partly Studio or Enterprise only	Yes
Read and send client messages	Partly Studio or Enterprise; Zapier can send, not read	Yes
Subscribe a client to a master program	Partly Studio or Enterprise, or Zapier on paid plans	Yes
Schedule appointments	Partly Studio or Enterprise only, not in Zapier	Yes
Log body stats for a client	Partly Studio or Enterprise only, not in Zapier	Yes
Tag, deactivate or reactivate clients	Partly Studio or Enterprise, or Zapier on paid plans	Yes

Sources: Using API and Webhooks With ABC Trainerize (help center) · What Is FitMetrics in ABC Trainerize? (help center) · Trainerize pricing · Trainerize triggers and actions on Zapier · Zapier MCP for ABC Trainerize · Automating Content Delivery with Product Automation (help center)

Common use cases

What can an AI agent do in Trainerize?

Cotlet is best for personal trainers and studio owners on Trainerize Grow or Pro who want their AI agent to handle check-ins, messages, programs and bookings without running or fixing a server.

Follow up with clients who stopped logging body stats Runs: Weekly

Find my full-access clients whose last body stats entry is more than two weeks old and draft a short check-in message for each. Leave out anyone who told me they are sick or traveling. Your agent calls list_clients, get_body_stats, list_conversations and send_message.
Summarize weekly check-in forms Runs: Weekly

Summarize the check-in forms submitted since last Monday. Flag anyone whose energy or motivation score dropped, anyone who mentions pain, and list who has not checked in. Your agent calls list_check_ins, get_client and list_clients.
Assign the next program when a client's program expires Runs: Weekly

Find clients whose main program ends in the next week or already ended. Suggest the next master program for each based on their goal and last check-in, and subscribe them after I approve, starting the day after the old one ends. Your agent calls list_clients, get_client, list_check_ins, list_master_programs and subscribe_to_program.
Book recurring appointments Runs: Weekly

Book a 1-on-1 with Sam every Tuesday at 7:00 for the next month. Your agent calls list_clients, list_appointments and schedule_appointment.
Draft replies to client messages Runs: Daily

Go through my unread Trainerize messages from today, check each client's program before answering, and draft replies I can approve one by one. Flag anything about pain or payments for me. Your agent calls list_conversations, get_conversation, get_client and send_message.
Log body stats after a session

Enter the weight and waist I measured for Alex at today's session. Your agent calls list_clients and log_body_stats.

Endpoints

What is the Trainerize API?

Cotlet's Trainerize API exposes 14 endpoints for your own Trainerize account: list clients, get client, get body stats, list check-ins, list conversations, get conversation, list master programs, list appointments, send message, subscribe to program, log body stats, schedule appointment, add client tags and set client status. The list_clients endpoint returns clients with client type, trainer, tags and last activity. Each endpoint takes simple JSON inputs like client_id, limit or search and works both as an MCP tool for agents and as a REST call for scripts.

All endpoints · 14 total

missing one? request an endpoint

POST

list_clients

Clients with client type, trainer, tags and last activity.

read

Lists the clients you can see, in the order Trainerize shows them. Deactivated clients are left out unless you ask for them with client_type. Filter by tag to get a group, or search by name or email. Pages hold up to 200 clients; pass next_cursor back as cursor for the next page.

POST /api/v1/trainerize/list_clients

Input

Input: list_clients
Parameter	Type	Description
client_type	enum	full_access, offline, basic, prospect, pending or deactivated. Default: all except deactivated.
tag	string	Only clients with this custom or auto client tag.
search	string	Match on name or email.
limit	integer	1 to 200. Default: 50.
cursor	string	Next page cursor from the previous call.

Example response

{
  "clients": [
    {
      "client_id": "4821937",
      "name": "Alex Rivera",
      "email": "alex@example.com",
      "client_type": "full_access",
      "trainer": "yourname",
      "tags": [
        "Challenge"
      ],
      "last_active": "2026-10-08T17:40:00Z"
    },
    {
      "client_id": "4821944",
      "name": "Sam Carter",
      "email": "sam@example.com",
      "client_type": "full_access",
      "trainer": "yourname",
      "tags": [
        "Challenge",
        "Online"
      ],
      "last_active": "2026-10-09T06:12:00Z"
    }
  ],
  "next_cursor": null
}

POST
get_client

Client profile: contact, client type, trainer, tags, goals, and main and add-on programs.
read
Returns one client profile with contact details, client type, trainer, tags, goals and the main and add-on programs the client is on. Use it before a message or a program change to see where the client stands.

POST /api/v1/trainerize/get_client

Input

Input: get_client

Parameter Type Description

client_id required string Client ID from list_clients.

Example response
```
{
  "client_id": "4821937",
  "name": "Alex Rivera",
  "email": "alex@example.com",
  "client_type": "full_access",
  "trainer": "yourname",
  "tags": [
    "Challenge"
  ],
  "goals": [
    "Lose 5 kg",
    "Run 5 km"
  ],
  "main_program": {
    "program_id": "552012",
    "name": "4-week Base"
  },
  "add_on_programs": []
}
```

POST

get_body_stats

Body weight, body fat, body measurements and caliper entries for a date range.

read

Returns the entries a client logged in the range, oldest first, grouped by date. Default range is the last 90 days.

POST /api/v1/trainerize/get_body_stats

Input

Input: get_body_stats
Parameter	Type	Description
client_id required	string	Client ID from list_clients.
from	date	Start date. Default: 90 days ago.
to	date	End date. Default: today.

Example response

{
  "client_id": "4821937",
  "entries": [
    {
      "date": "2026-09-12",
      "body_weight": 84.1,
      "waist": 90
    },
    {
      "date": "2026-09-26",
      "body_weight": 83.2,
      "waist": 89
    }
  ]
}

POST
list_check_ins

Check-in forms a client submitted, with each question and answer.
read
Lists submitted check-in forms, newest first, each with every question and the answer. Leave client_id empty to read all clients. Use since to read only what is new since your last run.

POST /api/v1/trainerize/list_check_ins

Input

Input: list_check_ins

Parameter Type Description

client_id string One client. Default: all clients.
since date Only check-ins submitted on or after this date.

Example response
```
{
  "check_ins": [
    {
      "check_in_id": "7710342",
      "client_id": "4821937",
      "client_name": "Alex Rivera",
      "submitted_at": "2026-10-06T08:15:00Z",
      "answers": [
        {
          "question": "How is your energy this week?",
          "answer": "2 out of 5"
        },
        {
          "question": "Anything getting in the way?",
          "answer": "Two late shifts, skipped Thursday."
        }
      ]
    }
  ]
}
```
POST
list_conversations

Your message conversations with clients and groups, newest first, with unread count.
read
Lists your conversations in the Trainerize messenger, newest first, with the other person or group, unread count and a preview of the last message. Set unread_only to see only what needs an answer.

POST /api/v1/trainerize/list_conversations

Input

Input: list_conversations

Parameter Type Description

unread_only boolean Only conversations with unread messages.
limit integer 1 to 100. Default: 30.

Example response
```
{
  "conversations": [
    {
      "conversation_id": "3390127",
      "with": {
        "client_id": "4821937",
        "name": "Alex Rivera"
      },
      "unread": 1,
      "last_message": "Can I swap lunges for something easier on my knee?",
      "updated_at": "2026-10-10T07:02:00Z"
    }
  ]
}
```
POST
get_conversation

Messages in one conversation, with sender, time and attachment names.
read
Returns the most recent messages of one conversation, oldest first, so your agent reads the thread in order. Attachments are listed by file name only.

POST /api/v1/trainerize/get_conversation

Input

Input: get_conversation

Parameter Type Description

conversation_id required string Conversation ID from list_conversations.
limit integer Most recent messages, 1 to 200. Default: 50.

Example response
```
{
  "conversation_id": "3390127",
  "messages": [
    {
      "from": "Alex Rivera",
      "body": "Can I swap lunges for something easier on my knee?",
      "sent_at": "2026-10-10T07:02:00Z",
      "attachments": []
    }
  ]
}
```
POST
list_master_programs

Master programs in your library, with program tags and subscriber count.
read
Lists the master programs in your library, with tags and how many clients are subscribed. Use the program_id with subscribe_to_program.

POST /api/v1/trainerize/list_master_programs

Input

Input: list_master_programs

Parameter Type Description

search string Match on program name.

Example response
```
{
  "programs": [
    {
      "program_id": "552031",
      "name": "6-week Shred",
      "tags": [
        "fat loss"
      ],
      "subscribers": 14
    },
    {
      "program_id": "552012",
      "name": "4-week Base",
      "tags": [
        "beginner"
      ],
      "subscribers": 31
    }
  ]
}
```
POST
list_appointments

Appointments on the schedule for a date range, with type, trainer and client.
read
Lists appointments in the range, earliest first, with type, trainer and client. Admins and managers can read another trainer's schedule with trainer_id; other roles see their own.

POST /api/v1/trainerize/list_appointments

Input

Input: list_appointments

Parameter Type Description

from required date Start date.
to required date End date.
trainer_id string Admins and managers: another trainer. Default: you.

Example response
```
{
  "appointments": [
    {
      "appointment_id": "90311102",
      "client_id": "4821944",
      "appointment_type": "1-on-1 Appointment",
      "start": "2026-10-13T08:00:00-04:00",
      "end": "2026-10-13T09:00:00-04:00",
      "trainer": "yourname"
    }
  ]
}
```
POST
send_message

Send a message to a client as you in the Trainerize messenger.
asks first write
Sends a message to one client in the Trainerize messenger under your name. The client sees it in the app. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/send_message

Input

Input: send_message

Parameter Type Description

client_id required string Client ID from list_clients.
body required string Message text.

Example response
```
{
  "conversation_id": "3390127",
  "message_id": "88120045",
  "status": "sent",
  "sent_at": "2026-10-10T09:05:00-04:00"
}
```

Input: list_check_ins
Parameter	Type	Description
client_id	string	One client. Default: all clients.
since	date	Only check-ins submitted on or after this date.

Input: list_conversations
Parameter	Type	Description
unread_only	boolean	Only conversations with unread messages.
limit	integer	1 to 100. Default: 30.

Input: get_conversation
Parameter	Type	Description
conversation_id required	string	Conversation ID from list_conversations.
limit	integer	Most recent messages, 1 to 200. Default: 50.

Input: list_master_programs
Parameter	Type	Description
search	string	Match on program name.

Input: list_appointments
Parameter	Type	Description
from required	date	Start date.
to required	date	End date.
trainer_id	string	Admins and managers: another trainer. Default: you.

POST

subscribe_to_program

Subscribe one or more clients to a master program from a start date.

asks first write

Subscribes the clients to a master program as their main program or as an add-on, starting on the date you give. The program appears in each client's app. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/subscribe_to_program

Input

Input: subscribe_to_program
Parameter	Type	Description
program_id required	string	Program ID from list_master_programs.
client_ids required	string[]	Clients to subscribe.
start_date required	date	First day of the program.
program_type	enum	main or add_on. Default: main.

Example response

{
  "program_id": "552031",
  "program_type": "main",
  "start_date": "2026-10-19",
  "subscribed": [
    {
      "client_id": "4821937",
      "status": "subscribed"
    },
    {
      "client_id": "4821944",
      "status": "subscribed"
    }
  ]
}

POST

log_body_stats

Enter body stats for a client on a date, in the client's units.

asks first write

Enters body stats for one client on one date, in the client's units. The entry shows in the client's progress. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/log_body_stats

Input

Input: log_body_stats
Parameter	Type	Description
client_id required	string	Client ID from list_clients.
date required	date	Day of the measurement.
stats required	object	Any of body_weight, body_fat_percent, waist, hips, chest, neck and other body measurements.

Example response

{
  "client_id": "4821937",
  "date": "2026-10-10",
  "status": "logged",
  "stats": {
    "body_weight": 82.4,
    "waist": 88
  }
}

POST

schedule_appointment

Book an appointment with a client, optionally weekly or monthly.

asks first write

Books an appointment of the type you name, with the client, at the start time you give. A weekly or monthly repeat creates one appointment per date up to repeat_until. Notes are visible to the client. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/schedule_appointment

Input

Input: schedule_appointment
Parameter	Type	Description
client_id required	string	Client ID from list_clients.
appointment_type required	string	Appointment type name, e.g. 1-on-1 Appointment.
start required	datetime	ISO 8601 with time zone.
repeat	enum	none, weekly or monthly. Default: none.
repeat_until	date	Last date of a repeating appointment.
notes	string	Appointment notes. The client can see them.

Example response

{
  "appointment_id": "90311284",
  "client_id": "4821937",
  "appointment_type": "1-on-1 Appointment",
  "start": "2026-10-13T07:00:00-04:00",
  "end": "2026-10-13T08:00:00-04:00",
  "repeat": "weekly",
  "occurrences": 5,
  "trainer": "yourname"
}

POST
add_client_tags

Add custom client tags to one or more clients.
asks first write
Adds existing custom client tags to the clients. Tags group clients for list_clients and for your own filters in Trainerize. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/add_client_tags

Input

Input: add_client_tags

Parameter Type Description

client_ids required string[] Clients to tag.
tags required string[] Existing custom client tag names.

Example response
```
{
  "tags": [
    "Challenge"
  ],
  "tagged": [
    "4821937",
    "4821944"
  ],
  "status": "tagged"
}
```
POST
set_client_status

Deactivate a client (they lose app access, history is kept) or reactivate them.
asks first write
Deactivates a client, who then loses access to the app while the history is kept, or reactivates a deactivated one. By default you confirm each call; you can switch that off for this tool.

POST /api/v1/trainerize/set_client_status

Input

Input: set_client_status

Parameter Type Description

client_id required string Client ID from list_clients.
status required enum deactivated or active.

Example response
```
{
  "client_id": "4821944",
  "status": "deactivated"
}
```

Input: add_client_tags
Parameter	Type	Description
client_ids required	string[]	Clients to tag.
tags required	string[]	Existing custom client tag names.

Setup

How do I connect Trainerize to Claude Code, Codex or Cursor?

Connecting Trainerize takes three steps: request access, sign in to Trainerize once, then add one MCP server or call the REST API with the same key.

MCP REST API

1
Create an account

Sign up and add Trainerize in the console. Your API key is there too.
2
Sign in to Trainerize once

Open the connect page from the console and sign in to Trainerize the way you always do. We keep the session, never your password, and you can revoke it anytime.
3
Add Cotlet to your agent
Claude Code Cursor Codex
Claude Code
```
claude mcp add --transport http cotlet \
  https://cotlet.dev/mcp/v1 \
  --header "Authorization: Bearer $COTLET_API_KEY"
```
Cursor
```
{
  "mcpServers": {
    "cotlet": {
      "url": "https://cotlet.dev/mcp/v1",
      "headers": {
        "Authorization": "Bearer ${COTLET_API_KEY}"
      }
    }
  }
}
```
Codex
```
# ~/.codex/config.toml
[mcp_servers.cotlet]
url = "https://cotlet.dev/mcp/v1"
bearer_token_env_var = "COTLET_API_KEY"
```
Paste the snippet for your client. The same server and key serve every app you connect, so you do this once.
4
Ask your agent
Prompt
```
Find my full-access clients whose last body stats entry is more than two weeks old and draft a short check-in message for each. Leave out anyone who told me they are sick or traveling.
```
Ask in plain words. Your agent finds the Trainerize tools on the server and calls them for you; anything that reaches other people waits for your OK unless you switch that off for a tool.

1
Export your API key
Shell
```
export COTLET_API_KEY="cotlet_..."
```
Your scripts use the same API key as your agent. Keep it in an environment variable, never in your code.

Call a tool

curl

curl https://cotlet.dev/api/v1/trainerize/schedule_appointment \
  -H "Authorization: Bearer $COTLET_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"client_id":"4821937","appointment_type":"1-on-1 Appointment","start":"2026-10-13T07:00:00-04:00","repeat":"weekly","repeat_until":"2026-11-10"}'

Every tool is a POST endpoint at /api/v1/trainerize/{tool}. Send its parameters as JSON, exactly as listed in the endpoints above.

Read the result

Example response · schedule_appointment

{
  "appointment_id": "90311284",
  "client_id": "4821937",
  "appointment_type": "1-on-1 Appointment",
  "start": "2026-10-13T07:00:00-04:00",
  "end": "2026-10-13T08:00:00-04:00",
  "repeat": "weekly",
  "occurrences": 5,
  "trainer": "yourname"
}

You get plain JSON back, ready for your script. A failed call costs nothing.

Why Cotlet

Why use Cotlet for Trainerize? Hosted, safe and kept working.

Built for agents
- One MCP server for every app you connect.
- The same tools as a REST API for scripts and cron jobs.
- Works with Claude Code, Codex and Cursor.
Your login stays yours
- You sign in to Trainerize yourself. We keep only the session, encrypted with AES-256.
- The model never sees a login.
- No stored passwords, no CAPTCHA solving, no MFA bypass.
You stay in control
- Pick read only, or read and write.
- Anything that reaches other people waits for your OK, unless you switch it off per tool.
- Revoke access in one click.
Kept working for you
- We test every integration daily.
- When Trainerize changes, the tool pauses until we fix it.
- Failed calls cost nothing.

Alternatives

Is there a Trainerize MCP server on GitHub?

No open-source Trainerize MCP server turned up. Zapier works on paid Trainerize plans and its MCP server can create clients, assign programs and send messages, but it cannot read messages, progress, check-ins or appointments.

Cotlet compared with a Zapier
	Zapier	Cotlet
Setup	Connect Trainerize in a Zapier account, then add Zapier MCP to your agent	Request access, sign in to Trainerize once in your browser, add one MCP server or API key
Reading data	Find a client by email; events arrive as triggers	Clients, messages, body stats, check-ins, programs and appointments
Write actions	Clients, tags, groups, programs, messages and files	Clients, tags, programs, messages, appointments and body stats, with your OK on each by default
When Trainerize changes	Zapier maintains its app	Our team tests it daily and fixes it for you; failed calls are free
When the session expires	Reconnect the account in Zapier	Your agent gets a link to sign in again
Where it runs	Zapier cloud, any MCP client	Hosted: Claude Code, Codex, Cursor, n8n and scripts, also on a schedule
Price	Free tier with limits, then a paid Zapier plan	Free 7-day trial with 5,000 credits, then credits per call

Which one fits you

Pick Cotlet if

you are not a developer, or you do not want to maintain a server
you need it to keep working when Trainerize changes, without checking it yourself
your agent or a script should run it on a schedule, also while your computer is off

Pick an open-source server if

you are comfortable installing, updating and fixing it yourself
you want the session to stay on your own computer
you only need it now and then, from one MCP client

For AI agents

Cotlet for Trainerize in plain text The facts on this page in one block: status, endpoints, access, pricing, contact.

Endpoint health

verified 2h ago

list_clients passing
get_client passing
get_body_stats passing
list_check_ins passing
list_conversations passing

+ 9 more endpoints

14/14 passing latest check self-healing

trainerize.txt

Trainerize has an API, but only on Studio and Enterprise plans or with the paid FitMetrics add-on (checked 10 Oct 2026). Grow and Pro trainers get Zapier, not the API, and there is no public API reference.
Cotlet provides a hosted MCP server and REST API for Trainerize: 14 tools (8 read, 6 write).
Access       Request access at https://cotlet.dev/app/signup?app=trainerize; we email the API key.

MCP server   https://cotlet.dev/mcp/v1
REST base    https://cotlet.dev/api/v1/trainerize
Auth         Authorization: Bearer <COTLET_API_KEY>. Listing endpoints and schemas needs no key; calling an endpoint needs one.
Tools        list_clients, get_client, get_body_stats, list_check_ins, list_conversations, get_conversation, list_master_programs, list_appointments, send_message, subscribe_to_program, log_body_stats, schedule_appointment, add_client_tags, set_client_status
Confirm      send_message, subscribe_to_program, log_body_stats, schedule_appointment, add_client_tags, set_client_status (by default the user approves each call; the user can switch this off per tool, e.g. for scheduled automations)
Markdown     https://cotlet.dev/integrations/trainerize-api-mcp-server.md

How access works:
1. The user requests access at https://cotlet.dev/app/signup?app=trainerize (Trainerize is pre-selected). Each request is reviewed and the API key is sent by email.
2. The user signs in to Trainerize once in a browser. An agent cannot do this step.
3. The API key goes into the MCP client or the REST call as a bearer token.

Fits: people who want a hosted Trainerize server that someone else maintains, including non-developers.

Policy: Cotlet never stores passwords, never solves CAPTCHAs, never bypasses MFA.
Company: legal details in the Terms of service at https://cotlet.dev/terms. Contact contact@cotlet.dev.
Session: the user signs in to Trainerize in a browser; Cotlet keeps only the session, AES-256 encrypted, revocable in the dashboard at any time.
Terms: the user stays responsible for following Trainerize's terms; Cotlet is not affiliated with Trainerize.

Full page as Markdown

Automations

Can Trainerize automations run on a schedule in n8n, Make or Zapier?

Yes. Cotlet does not replace your automation platform: it gives it a Trainerize connection it does not have, with the same API key as your agent. Write actions ask for your OK by default; switch that off in your dashboard for the tools you choose, for example to follow up with clients who stopped logging body stats, and the schedule runs on its own. Cotlet runs in the cloud, so it keeps going while your computer is off.

Where to run Trainerize automations through Cotlet, and how to schedule them
Where	How to connect	How to schedule
Your AI agent	Add https://cotlet.dev/mcp/v1 with your API key.	A scheduled agent run, for example a Claude Code routine.
n8n	MCP Client node with https://cotlet.dev/mcp/v1, or an HTTP Request node to https://cotlet.dev/api/v1/trainerize/{tool}.	Schedule Trigger node.
Make	HTTP module: POST https://cotlet.dev/api/v1/trainerize/{tool} with an Authorization: Bearer header and a JSON body.	Scenario schedule.
Zapier	Webhooks by Zapier: POST https://cotlet.dev/api/v1/trainerize/{tool} with the same header and body.	Schedule by Zapier trigger.
Your own script	POST https://cotlet.dev/api/v1/trainerize/{tool} with your API key.	cron or GitHub Actions.

Pricing & limits

How much does the Trainerize API cost?

Free 7-day trial with 5,000 credits, no card needed. After that, the Trainerize API comes with the Cotlet plan, from $29 a month for 3,000 credits, with no limit on apps. Each month's credits stay valid for 3 months, so unused credits add up.

See full pricing

Cotlet plan sizes: price, monthly credits and price per credit
Size	Price	Credits / month	Per credit
Solo	$29/mo	3,000	about $0.0097
Pro	$99/mo	12,000	about $0.0083
Agency	$299/mo	40,000	$0.0075

Each successful call uses credits for the work it takes; failed calls and timeouts cost nothing. A hard spend cap is on by default. Authenticate with the Authorization: Bearer header.

About Cotlet

How Cotlet holds your access

Cotlet hosts MCP servers and REST APIs for apps with no usable API. Your agent works in your own Trainerize account.

Company details: The legal name, address and registration numbers of the company behind Cotlet are in the Terms of service. Terms
Your session: You sign in to Trainerize yourself, in your browser. We keep only the session, never your password: encrypted with AES-256 in an EU vault, isolated to your account and used only when your agent calls a Trainerize tool you allowed. When it expires, your agent gives you a link to sign in again. Security
Revoking access: Disconnect Trainerize in your dashboard: the session is deleted and access ends at once. Actions that reach other people wait for your OK unless you switch that off per tool.
What we never do: Store passwords, solve CAPTCHAs or bypass MFA.
Trainerize's terms: You use your own Trainerize account and stay responsible for following Trainerize's terms. Cotlet is independent and not affiliated with Trainerize. Terms
Contact: Questions about the company, security or an app: contact@cotlet.dev

About Cotlet

Frequently asked questions

How do I get access?

Request access and pick Trainerize. Cotlet reviews each request and emails you your API key.

Do I need to be technical?

No. You sign in to Trainerize once in your browser and paste one command into your agent, or one URL into n8n. Your agent can walk you through it. There is no server to install, update or fix.

Is a hosted server safe? My Trainerize session would leave my computer.

Cotlet keeps your Trainerize session encrypted with AES-256 in an EU vault, isolated to your account and used only for the tools you allow: read only, or read and write. The AI model never sees it, and you revoke it in one click. A local server keeps the same session in a file on your computer, readable by any program you run, and needs a fresh sign-in whenever it expires.

Do I need a Studio or Enterprise plan?

No. Cotlet works in your own Trainerize account and does not use the API, which Trainerize limits to Studio and Enterprise plans or the FitMetrics add-on (checked 10 Oct 2026). Some tools depend on your role: reading another trainer's schedule needs an admin or manager.

Can my agent post or send messages in Trainerize without asking me?

No. Every call to send_message, subscribe_to_program, log_body_stats, schedule_appointment, add_client_tags or set_client_status waits for your OK by default. For scheduled automations you can switch confirmation off per tool in your dashboard, for example only for approvals.

Can I use the Trainerize API in n8n?

Yes. Add https://cotlet.dev/mcp/v1 with your API key in n8n's MCP Client node, or call https://cotlet.dev/api/v1/trainerize/{tool} from the HTTP Request node.

Give your agent access to Trainerize.

Request access and pick it. We review each request and email you your API key. Free 7-day trial with 5,000 credits, no card needed.

Request access

Does Trainerize have an official API?

What can an AI agent do in Trainerize?

Follow up with clients who stopped logging body stats Runs: Weekly

Summarize weekly check-in forms Runs: Weekly

Assign the next program when a client's program expires Runs: Weekly

Book recurring appointments Runs: Weekly

Draft replies to client messages Runs: Daily

Log body stats after a session

What is the Trainerize API?

list_clients

get_client

get_body_stats

list_check_ins

list_conversations

get_conversation

list_master_programs

list_appointments

send_message

subscribe_to_program

log_body_stats

schedule_appointment

add_client_tags

set_client_status

How do I connect Trainerize to Claude Code, Codex or Cursor?

Connect Trainerize over MCP

Create an account

Sign in to Trainerize once

Add Cotlet to your agent

Ask your agent

Call Trainerize over REST

Export your API key

Call a tool

Read the result

Why use Cotlet for Trainerize? Hosted, safe and kept working.

Built for agents

Your login stays yours

You stay in control

Kept working for you

Is there a Trainerize MCP server on GitHub?

Which one fits you

Cotlet for Trainerize in plain text The facts on this page in one block: status, endpoints, access, pricing, contact.

Can Trainerize automations run on a schedule in n8n, Make or Zapier?

How much does the Trainerize API cost?

How Cotlet holds your access

Frequently asked questions

How do I get access?

Do I need to be technical?

Is a hosted server safe? My Trainerize session would leave my computer.

Do I need a Studio or Enterprise plan?

Can my agent post or send messages in Trainerize without asking me?

Can I use the Trainerize API in n8n?

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