We're excited to invite you to be among the first to test an entirely new way to interact with your training data. We've built a Model Context Protocol (MCP) communication protocol that connects your COROS account directly to your preferred AI platform. This feature allows you to use natural conversation to analyze your training data, identify trends and patterns, and an infinite number of additional possibilities. With the MCP tool, your ability to work with large data and create dashboards, spreadsheets, and more – just got a whole lot faster.

This MCP tool is a "read-only" integration. Right now, it can't write anything to your calendar or create new workouts, but it can analyze and process your existing data. We expect to have additional updates rolled out to the MCP tool like "write training plan" permissions in the near future.

What we're most excited about is seeing how you use this tool, and what you're able to build. To join the conversation, visit our Reddit page [here] to share your experience. View the instructions below to get started.

First: What is this?

An MCP is a standardized "plug" that allows an AI model to securely connect with your local files, databases, and third-party tools so it can understand your specific data and perform tasks directly within those systems. This MCP tool for COROS allows you to ask simple questions like you would ask AI or search on Google, but it will allow the AI to directly access your training history:

For example:

"How did my running look this month?"

"I have a race in 6 weeks, am I ready?"

The AI reads your COROS data and answers you.

What you'll need before you start

• A COROS account (you have one if you use the COROS app)
• A subscription to ChatGPT Plus or Claude Pro. MCP features require a paid plan on most platforms.

Step 1 : Find your region's link

Copy the link that matches where you live:

Step 2 : Connect it to your AI tool

ChatGPT

1. Open ChatGPT → Settings → Beta features
2. Turn on MCP Servers
3. Click Add MCP Server
4. Paste the link from Step 1
5. Click Authorize and log into your COROS account
6. Done — go ask it something

Claude (Desktop app)

1. Open Claude → click the gear icon (Settings)
2. Go to Extensions → MCP Servers
3. Click Add MCP Server → select Custom Server
4. Paste the link from Step 1
5. Click Save
6. Done — go ask it something

Step 3 : Try it

Go back to your AI chat and try typing:

"Show me my workouts from the past two weeks"

If it responds with your data, you're all set.

Troubleshooting

It says "connection failed"→ Double-check you copied the right link for your region (see Step 1)

It asks you to log in but nothing happens→ Make sure your COROS account works at coros.com first

You don't see "MCP Servers" in settings→ You likely need a Plus/PRO subscription for this feature on your platform. Free plans often don't support MCP.

Which platforms support MCP?→ ChatGPT, Claude, and Cursor all support it. The steps are similar — look for Settings → Extensions → MCP in whichever tool you use.

What about Gemini? Gemini doesn't currently support custom MCP connectors through the standard chat interface (gemini.google.com) the way ChatGPT and Claude do. With those two, it's a simple paste-the-URL, authorize, and go — Gemini's consumer app doesn't have that yet.

If you're comfortable working in a terminal, you can still connect via the Gemini CLI. Follow Google's setup guide here and use your region's COROS MCP link from Step 1 as the server URL. We'll update this guide if and when Google adds MCP connector support to the Gemini chat app.

Privacy and Data Disclaimer

This integration does not create any new security or privacy risks beyond those that already exist when using your COROS account and your chosen AI platform separately. It is a structured connection layer that allows the two systems to communicate in a controlled, permission-based way. The same standards of account security, data protection, and platform privacy continue to apply.

Your COROS data remains governed by COROS privacy and security protections, and your AI interactions remain governed by the policies, permissions, and settings of the AI platform you choose to use. In other words, connecting through MCP does not change the underlying rules around how your data is protected — it simply allows approved data and actions to move between systems in a more useful and efficient way.

Access is only granted through explicit user authorization. You decide whether to connect your account, and the connection only operates within the permissions you approve. Depending on the capabilities enabled, that may include both read access to analyze training data and write access for supported actions within the connected experience. Those permissions are not open-ended; they are limited to the scope of the integration and the controls provided by COROS and the AI platform.

Importantly, this integration is not a backdoor into your account, and it does not bypass existing authentication, privacy controls, or security safeguards. It uses the same identity, authorization, and protection principles that already apply across secure connected services.

In practical terms, users should think of this as a secure extension of the tools they already use: your data protections remain in place, your permissions still matter, and you remain in control of what is connected and what actions are allowed.