S

Strava MCP

This project is a Strava API bridge service based on TypeScript. It exposes Strava's sports data functions as tools callable by LLM through the MCP standard, supporting various sports data interaction functions such as activity statistics, route export, and heart rate analysis.
2.5 points
50

What is the Strava MCP service?

This is an intelligent service that connects the Strava sports platform with an AI assistant. It can convert your sports data (such as running and cycling records) into a format understandable by AI, allowing you to query and analyze sports performance through natural language.

How to use this service?

Simply install and configure it, then ask your AI assistant questions about Strava data, such as 'Show me my running data from last week' or 'Analyze the power output of my last cycling session'.

Applicable scenarios

Suitable for athletes and fitness enthusiasts to use AI for scenarios such as training data analysis, performance tracking, route planning, and sports social interaction.

Main features

Activity data queryGet detailed sports record information, including indicators such as distance, duration, heart rate, and power.
Route exportExport saved routes as GPX/TCX format files for easy import into navigation devices.
Segment analysisView detailed data and historical performance records of specific road segments.
Stream dataGet high-precision time-series data (heart rate, power, cadence, etc.) for in-depth analysis.

Advantages and limitations

Advantages
Natural language interaction - Query complex sports data by speaking
Automated analysis - AI automatically generates training insights and suggestions
Data visualization - Automatically create professional charts to display sports performance
Seamless integration - Connect directly with an existing Strava account
Limitations
A Strava premium account is required to access complete data
Some historical data may be incomplete
A storage path needs to be pre - configured for exporting files

How to use

Install the service
Install the service package via npm and build the project
Configure the AI assistant
Add Strava service settings to the AI assistant configuration file
Strava authentication
Run the authentication script to complete the connection to your Strava account
Start querying
You can start querying sports data in natural language after restarting the AI assistant

Usage examples

Training performance analysisLet the AI coach analyze the data of your last high - intensity training session
Route planningFind and export routes suitable for long - distance running

Frequently Asked Questions

Do I need a paid Strava account?
How long is the data update delay?
What sports types are supported?

Related resources

GitHub repository
Project source code and latest updates
Strava developer documentation
Official API reference documentation
MCP protocol description
Model Context Protocol technical specification
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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