Интеграция Strava API с Model Context Protocol (MCP) SDK
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Интеграция Strava API с Model Context Protocol (MCP) SDK
Интеграция для анализа тренировок и получения рекомендаций на основе данных Strava с использованием Model Context Protocol SDK.
🚀 Возможности
- Анализ тренировок из Strava
- Рекомендации по тренировкам
- Автоматическое обновление токенов
- Rate limiting для API запросов
📋 Требования
- Python 3.10+
- Claude Desktop
- Strava аккаунт
- uv (рекомендуется)
⚙️ Установка
# 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]"
Установка MCP SDK
uv add "mcp[cli]"
🔧 Настройка
Настройка Strava API
- Перейдите на страницу настроек API
- Создайте приложение:
- Application Name: MCP Strava Integration
- Category: Training Analysis
- Website: http://localhost
- Authorization Callback Domain: localhost
Настройка окружения
-
Создайте файл с переменными окружения:
cp .env-template .env -
Получите токены доступа:
python scripts/auth.py -
Проверьте настройку:
mcp dev src/server.py curl -X GET "http://localhost:8000/activities"
📚 API и примеры
Ресурсы и инструменты
| Тип | Название | Описание |
|---|---|---|
| Ресурс | strava://activities |
Список активностей |
| Ресурс | strava://activities/{id} |
Детали активности |
| Ресурс | strava://athlete/zones |
Тренировочные зоны |
| Ресурс | strava://athlete/clubs |
Клубы атлета |
| Ресурс | strava://gear/{gear_id} |
Информация о снаряжении |
| Инструмент | analyze_activity(activity_id) |
Анализ тренировки |
| Инструмент | analyze_training_load(activities) |
Анализ нагрузки |
| Инструмент | get_activity_recommendations() |
Рекомендации |
Примеры использования
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}
]
}
}
"""
🛠 Разработка
CI/CD и безопасность
Проверки в GitHub Actions
| Тип | Инструмент | Описание |
|---|---|---|
| Линтинг | ruff | Форматирование и анализ кода |
| Тесты | pytest | Unit и интеграционные тесты |
| Покрытие | pytest-cov | Отчет о покрытии кода |
Безопасность и секреты
-
Защита токенов:
.envв.gitignore- GitHub Secrets для CI/CD
- Rate limiting: 100 запросов/15 мин
-
Настройка секретов:
# В GitHub: Settings → Secrets → Actions STRAVA_CLIENT_ID=<client_id> STRAVA_CLIENT_SECRET=<client_secret> STRAVA_REFRESH_TOKEN=<refresh_token>
Contributing
-
Форкните репозиторий
-
Установите зависимости:
uv pip install -e ".[dev]" -
Создайте ветку:
git checkout -b feature/name -
Проверьте изменения:
ruff format . ruff check . pytest --cov=src -
Создайте Pull Request
📫 Поддержка
- GitHub Issues: создать issue
- Telegram: @greg_kisel
📄 Лицензия
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