remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Integrations

Allows analysis of Strava workouts and provides training recommendations based on Strava data using the Model Context Protocol SDK

Strava API integration with Model Context Protocol (MCP) SDK

Integration for training analysis and recommendations based on Strava data using the Model Context Protocol SDK.

🚀 Features

Analysis of workouts from Strava
Training Recommendations
Automatic token update
Rate limiting for API requests

📋 Requirements

Python 3.10+
Claude Desktop
Strava account
uv (recommended)

⚙️ Installation

# Клонируем репозиторий
git clone https://github.com/rbctmz/mcp-server-strava.git
cd mcp-server-strava

# Установка через uv (рекомендуется)
curl -LsSf https://astral.sh/uv/install.sh | sh
uv pip install .

# Установка в режиме разработки
uv pip install -e ".[dev]"

Installing MCP SDK

uv add "mcp[cli]"

🔧 Setting

Setting up Strava API

Go to the API settings page
Create an application:
- Application Name: MCP Strava Integration
- Category: Training Analysis
- Website: http://localhost
- Authorization Callback Domain: localhost

Setting up the environment

Create a file with environment variables:
cp .env-template .env
Get access tokens:
python scripts/auth.py
Check the setting:
mcp dev src/server.py curl -X GET "http://localhost:8000/activities"

📚 API and examples

Resources and Tools

Type	Name	Description
Resource	`strava://activities`	List of activities
Resource	`strava://activities/{id}`	Activity details
Resource	`strava://athlete/zones`	Training zones
Resource	`strava://athlete/clubs`	Athlete's clubs
Resource	`strava://gear/{gear_id}`	Equipment Information
Tool	`analyze_activity(activity_id)`	Training Analysis
Tool	`analyze_training_load(activities)`	Load analysis
Tool	`get_activity_recommendations()`	Recommendations

Examples of use

from mcp import ClientSession

# Получение активностей
async with ClientSession() as session:
    activities = await session.read_resource("strava://activities")
    activity = await session.read_resource("strava://activities/12345678")

# Анализ тренировки
result = analyze_activity(activity_id="12345678")
"""
{
    "type": "Run",
    "distance": 5000,
    "moving_time": 1800,
    "analysis": {
        "pace": 5.5,  # мин/км
        "effort": "Средняя"
    }
}
"""

# Анализ нагрузки
summary = analyze_training_load(activities)
"""
{
    "activities_count": 10,
    "total_distance": 50.5,  # км
    "total_time": 5.2,      # часы
    "heart_rate_zones": {
        "easy": 4,    # ЧСС < 120
        "medium": 4,  # ЧСС 120-150
        "hard": 2     # ЧСС > 150
    }
}
"""

# Получение тренировочных зон
async with ClientSession() as session:
    zones = await session.read_resource("strava://athlete/zones")
    """
    {
        "heart_rate": {
            "custom_zones": true,
            "zones": [
                {"min": 0, "max": 120, "name": "Z1 - Recovery"},
                {"min": 120, "max": 150, "name": "Z2 - Endurance"},
                {"min": 150, "max": 170, "name": "Z3 - Tempo"},
                {"min": 170, "max": 185, "name": "Z4 - Threshold"},
                {"min": 185, "max": -1, "name": "Z5 - Anaerobic"}
            ]
        },
        "power": {
            "zones": [
                {"min": 0, "max": 180},
                {"min": 181, "max": 250},
                {"min": 251, "max": 300},
                {"min": 301, "max": 350},
                {"min": 351, "max": -1}
            ]
        }
    }
    """

🛠 Development

CI/CD and Security

Checks in GitHub Actions

Type	Tool	Description
Linting	ruff	Code formatting and analysis
Tests	pytest	Unit and integration tests
Coating	pytest-cov	Code Coverage Report

Security and Secrets

Token protection:
- .env to .gitignore
- GitHub Secrets for CI/CD
- Rate limiting: 100 requests/15 min
Setting up secrets:
# В GitHub: Settings → Secrets → Actions STRAVA_CLIENT_ID=<client_id> STRAVA_CLIENT_SECRET=<client_secret> STRAVA_REFRESH_TOKEN=<refresh_token>