[{"_1":2,"_315":-5,"_316":-5},"loaderData",{"_3":4,"_32":33,"_34":35,"_255":256},"root",{"_5":6,"_17":18},"toasts",[7,14],{"_8":9,"_10":11,"_12":13},"uid","0196b4d8-cac2-71e4-af70-6580460390ed","title","You need to sign in to access this page","type","error",{"_8":15,"_10":16,"_12":13},"0196b4d8-cc2f-742e-9b79-1a59b63515e5","This MCP server does not support inspection","visitor",{"_19":20,"_21":22},"viewportWidth",1280,"visitorSession",{"_23":24,"_26":27,"_28":-5,"_29":30,"_31":-5},"attributes",[25],"BOT","id",6172344,"membership","referenceId","0196b4d8-ca7d-7070-a9a0-63b68698b636","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_36":37,"_82":-5,"_83":38,"_39":84,"_173":174,"_254":142},"availableLocales",[38,50,57,63,69,75],{"_39":40,"_43":47,"_48":49},"mcpServer",{"_41":42,"_43":44,"_45":46},"description","Integration of Strava API with Model Context Protocol SDK","name","mcp-server-strava","readme","# Strava API integration with Model Context Protocol (MCP) SDK\n\n![CI](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)![Codecs](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)![Python](https://img.shields.io/badge/python-3.10+-blue.svg)![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)![Ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\nIntegration for training analysis and recommendations based on Strava data using the Model Context Protocol SDK.\n\n## 🚀 Features\n\n* Analysis of workouts from Strava\n* Training Recommendations\n* Automatic token update\n* Rate limiting for API requests\n\n## 📋 Requirements\n\n* Python 3.10+\n* [Claude Desktop](https://claude.ai/desktop)\n* [Strava](https://www.strava.com) account\n* [uv](https://github.com/astral-sh/uv) (recommended)\n\n## ⚙️ Installation\n\n```bash\n# Клонируем репозиторий\ngit clone https://github.com/rbctmz/mcp-server-strava.git\ncd mcp-server-strava\n\n# Установка через uv (рекомендуется)\ncurl -LsSf https://astral.sh/uv/install.sh | sh\nuv pip install .\n\n# Установка в режиме разработки\nuv pip install -e \".[dev]\"\n```\n\n### Installing MCP SDK\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 Setting\n\n### Setting up Strava API\n\n1. Go to [the API settings page](https://www.strava.com/settings/api)\n2. Create an application:\n * Application Name: MCP Strava Integration\n * Category: Training Analysis\n * Website: \n * Authorization Callback Domain: localhost\n\n### Setting up the environment\n\n1. Create a file with environment variables:\n\n ```bash\n cp .env-template .env\n ```\n\n2. Get access tokens:\n\n ```bash\n python scripts/auth.py\n ```\n\n3. Check the setting:\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 API and examples\n\n### Resources and Tools\n\n| Type | Name | Description |\n| -------- | ----------------------------------- | --------------------- |\n| Resource | `strava://activities` | List of activities |\n| Resource | `strava://activities/{id}` | Activity details |\n| Resource | `strava://athlete/zones` | Training zones |\n| Resource | `strava://athlete/clubs` | Athlete's clubs |\n| Resource | `strava://gear/{gear_id}` | Equipment Information |\n| Tool | `analyze_activity(activity_id)` | Training Analysis |\n| Tool | `analyze_training_load(activities)` | Load analysis |\n| Tool | `get_activity_recommendations()` | Recommendations |\n\n### Examples of use\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 Development\n\n### CI/CD and Security\n\n* ![Coverage](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n* ![Tests](https://img.shields.io/badge/tests-15%20passed-green.svg)\n* ![Ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### Checks in GitHub Actions\n\n| Type | Tool | Description |\n| ------- | ---------- | ---------------------------- |\n| Linting | ruff | Code formatting and analysis |\n| Tests | pytest | Unit and integration tests |\n| Coating | pytest-cov | Code Coverage Report |\n\n#### Security and Secrets\n\n1. Token protection:\n\n * `.env` to `.gitignore`\n * GitHub Secrets for CI/CD\n * Rate limiting: 100 requests/15 min\n\n2. Setting up secrets:\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### Contributing\n\n1. Fork the repository\n\n2. Install dependencies: `uv pip install -e \".[dev]\"`\n\n3. Create a branch: `git checkout -b feature/name`\n\n4. Check the changes:\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. Create a Pull Request\n\n## 📫 Support\n\n* GitHub Issues: [create issue](https://github.com/rbctmz/mcp-server-strava/issues)\n* Telegram: [@greg\\_kisel](https://t.me/greg_kisel)\n\n## 📄 License\n\n[MIT](LICENSE)","English","tag","en-US",{"_39":51,"_43":55,"_48":56},{"_41":52,"_43":53,"_45":54},"Integración de la API de Strava con el SDK del protocolo de contexto de modelo","servidor mcp-strava","# Integración de la API de Strava con el SDK del Protocolo de Contexto de Modelo (MCP)\n\n![CI](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)![Códecs](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)![Pitón](https://img.shields.io/badge/python-3.10+-blue.svg)![Licencia: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)![Fallar](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\nIntegración para análisis de entrenamiento y recomendaciones basadas en datos de Strava utilizando el SDK Model Context Protocol.\n\n## 🚀 Características\n\n* Análisis de entrenamientos de Strava\n* Recomendaciones de formación\n* Actualización automática de tokens\n* Limitación de velocidad para solicitudes de API\n\n## 📋 Requisitos\n\n* Python 3.10+\n* [Escritorio de Claude](https://claude.ai/desktop)\n* Cuenta de [Strava](https://www.strava.com)\n* [uv](https://github.com/astral-sh/uv) (recomendado)\n\n## ⚙️ Instalación\n\n```bash\n# Клонируем репозиторий\ngit clone https://github.com/rbctmz/mcp-server-strava.git\ncd mcp-server-strava\n\n# Установка через uv (рекомендуется)\ncurl -LsSf https://astral.sh/uv/install.sh | sh\nuv pip install .\n\n# Установка в режиме разработки\nuv pip install -e \".[dev]\"\n```\n\n### Instalación del SDK de MCP\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 Configuración\n\n### Configuración de la API de Strava\n\n1. Vaya a [la página de configuración de la API](https://www.strava.com/settings/api)\n2. Crear una aplicación:\n * Nombre de la aplicación: Integración de MCP Strava\n * Categoría: Análisis de entrenamiento\n * Sitio web: \n * Dominio de devolución de llamada de autorización: localhost\n\n### Configuración del entorno\n\n1. Crea un archivo con variables de entorno:\n\n ```bash\n cp .env-template .env\n ```\n\n2. Obtener tokens de acceso:\n\n ```bash\n python scripts/auth.py\n ```\n\n3. Compruebe la configuración:\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 API y ejemplos\n\n### Recursos y herramientas\n\n| Tipo | Nombre | Descripción |\n| ----------- | ----------------------------------- | ------------------------- |\n| Recurso | `strava://activities` | Lista de actividades |\n| Recurso | `strava://activities/{id}` | Detalles de la actividad |\n| Recurso | `strava://athlete/zones` | Zonas de entrenamiento |\n| Recurso | `strava://athlete/clubs` | Clubes de atletas |\n| Recurso | `strava://gear/{gear_id}` | Información del equipo |\n| Herramienta | `analyze_activity(activity_id)` | Análisis de entrenamiento |\n| Herramienta | `analyze_training_load(activities)` | Análisis de carga |\n| Herramienta | `get_activity_recommendations()` | Recomendaciones |\n\n### Ejemplos de uso\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 Desarrollo\n\n### CI/CD y seguridad\n\n* ![Cobertura](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n* ![Pruebas](https://img.shields.io/badge/tests-15%20passed-green.svg)\n* ![Fallar](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### Comprobaciones en acciones de GitHub\n\n| Tipo | Herramienta | Descripción |\n| ------------- | ---------------- | ---------------------------------- |\n| Pelusa | fallar | Formato y análisis de código |\n| Pruebas | prueba de python | Pruebas unitarias y de integración |\n| Revestimiento | pytest-cov | Informe de cobertura de código |\n\n#### Seguridad y secretos\n\n1. Protección de token:\n\n * `.env` a `.gitignore`\n * Secretos de GitHub para CI/CD\n * Limitación de velocidad: 100 solicitudes/15 min\n\n2. Configuración de secretos:\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### Contribuyendo\n\n1. Bifurcar el repositorio\n\n2. Instalar dependencias: `uv pip install -e \".[dev]\"`\n\n3. Crear una rama: `git checkout -b feature/name`\n\n4. Comprueba los cambios:\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. Crear una solicitud de extracción\n\n## 📫 Soporte\n\n* Problemas de GitHub: [crear un problema](https://github.com/rbctmz/mcp-server-strava/issues)\n* Telegrama: [@greg\\_kisel](https://t.me/greg_kisel)\n\n## 📄 Licencia\n\n[Instituto Tecnológico de Massachusetts (MIT)](LICENSE)","Spanish","es-ES",{"_39":58,"_43":61,"_48":62},{"_41":59,"_43":44,"_45":60},"Strava APIとモデルコンテキストプロトコルSDKの統合","# Strava API と Model Context Protocol (MCP) SDK の統合\n\n![CI](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)![コーデック](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)![パイソン](https://img.shields.io/badge/python-3.10+-blue.svg)![ライセンス: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)![ラフ](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\nModel Context Protocol SDK を使用して、Strava データに基づくトレーニング分析と推奨事項を統合します。\n\n## 🚀 機能\n\n* Stravaからのワークアウトの分析\n* トレーニングの推奨事項\n* 自動トークン更新\n* APIリクエストのレート制限\n\n## 📋 要件\n\n* Python 3.10以上\n* [クロードデスクトップ](https://claude.ai/desktop)\n* [Strava](https://www.strava.com)アカウント\n* [uv](https://github.com/astral-sh/uv) （推奨）\n\n## ⚙️ インストール\n\n```bash\n# Клонируем репозиторий\ngit clone https://github.com/rbctmz/mcp-server-strava.git\ncd mcp-server-strava\n\n# Установка через uv (рекомендуется)\ncurl -LsSf https://astral.sh/uv/install.sh | sh\nuv pip install .\n\n# Установка в режиме разработки\nuv pip install -e \".[dev]\"\n```\n\n### MCP SDKのインストール\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 設定\n\n### Strava APIの設定\n\n1. [API設定ページ](https://www.strava.com/settings/api)へ移動\n2. アプリケーションを作成します。\n * アプリケーション名: MCP Strava 統合\n * カテゴリー: トレーニング分析\n * ウェブサイト: \n * 承認コールバックドメイン: localhost\n\n### 環境の設定\n\n1. 環境変数を含むファイルを作成します。\n\n ```bash\n cp .env-template .env\n ```\n\n2. アクセストークンを取得します。\n\n ```bash\n python scripts/auth.py\n ```\n\n3. 設定を確認してください:\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 APIと例\n\n### リソースとツール\n\n| タイプ | 名前 | 説明 |\n| ---- | ----------------------------------- | ---------- |\n| リソース | `strava://activities` | 活動リスト |\n| リソース | `strava://activities/{id}` | アクティビティの詳細 |\n| リソース | `strava://athlete/zones` | トレーニングゾーン |\n| リソース | `strava://athlete/clubs` | アスリートクラブ |\n| リソース | `strava://gear/{gear_id}` | 機器情報 |\n| 道具 | `analyze_activity(activity_id)` | トレーニング分析 |\n| 道具 | `analyze_training_load(activities)` | 負荷解析 |\n| 道具 | `get_activity_recommendations()` | 推奨事項 |\n\n### 使用例\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 開発\n\n### CI/CDとセキュリティ\n\n* ![カバレッジ](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n* ![テスト](https://img.shields.io/badge/tests-15%20passed-green.svg)\n* ![ラフ](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### GitHub Actionsでのチェック\n\n| タイプ | 道具 | 説明 |\n| ------ | ---------- | ------------- |\n| リンティング | ラフ | コードのフォーマットと分析 |\n| テスト | pytest | ユニットテストと統合テスト |\n| コーティング | pytest-cov | コードカバレッジレポート |\n\n#### セキュリティと秘密\n\n1. トークン保護:\n\n * `.env`から`.gitignore`へ\n * CI/CD のための GitHub Secrets\n * レート制限: 100 リクエスト/15 分\n\n2. シークレットの設定:\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### 貢献\n\n1. リポジトリをフォークする\n\n2. 依存関係をインストールします: `uv pip install -e \".[dev]\"`\n\n3. ブランチを作成する: `git checkout -b feature/name`\n\n4. 変更を確認します。\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. プルリクエストを作成する\n\n## 📫 サポート\n\n* GitHub Issues:[問題を作成する](https://github.com/rbctmz/mcp-server-strava/issues)\n* テレグラム: [@greg\\_kisel](https://t.me/greg_kisel)\n\n## 📄 ライセンス\n\n[マサチューセッツ工科大学](LICENSE)","Japanese","ja-JP",{"_39":64,"_43":67,"_48":68},{"_41":65,"_43":44,"_45":66},"Strava API와 Model Context Protocol SDK 통합","# Strava API와 MCP(Model Context Protocol) SDK 통합\n\n![씨아이](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)![코덱](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)![파이썬](https://img.shields.io/badge/python-3.10+-blue.svg)![라이센스: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)![주름 옷깃](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\nModel Context Protocol SDK를 사용하여 Strava 데이터를 기반으로 한 교육 분석 및 추천을 통합합니다.\n\n## 🚀 특징\n\n* Strava에서 운동 분석\n* 교육 권장 사항\n* 자동 토큰 업데이트\n* API 요청에 대한 속도 제한\n\n## 📋 요구 사항\n\n* 파이썬 3.10+\n* [클로드 데스크탑](https://claude.ai/desktop)\n* [Strava](https://www.strava.com) 계정\n* [uv](https://github.com/astral-sh/uv) (추천)\n\n## ⚙️ 설치\n\n지엑스피1\n\n### MCP SDK 설치\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 설정\n\n### Strava API 설정\n\n1. [API 설정 페이지](https://www.strava.com/settings/api) 로 이동\n2. 애플리케이션을 생성하세요:\n * 애플리케이션 이름: MCP Strava 통합\n * 카테고리: 교육 분석\n * 웹사이트: \n * 권한 부여 콜백 도메인: localhost\n\n### 환경 설정\n\n1. 환경 변수가 있는 파일을 만듭니다.\n\n ```bash\n cp .env-template .env\n ```\n\n2. 액세스 토큰을 받으세요:\n\n ```bash\n python scripts/auth.py\n ```\n\n3. 설정을 확인하세요:\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 API 및 예제\n\n### 리소스 및 도구\n\n| 유형 | 이름 | 설명 |\n| -- | ----------------------------------- | -------- |\n| 의지 | `strava://activities` | 활동 목록 |\n| 의지 | `strava://activities/{id}` | 활동 세부 정보 |\n| 의지 | `strava://athlete/zones` | 훈련 구역 |\n| 의지 | `strava://athlete/clubs` | 운동선수 클럽 |\n| 의지 | `strava://gear/{gear_id}` | 장비 정보 |\n| 도구 | `analyze_activity(activity_id)` | 훈련 분석 |\n| 도구 | `analyze_training_load(activities)` | 부하 분석 |\n| 도구 | `get_activity_recommendations()` | 추천사항 |\n\n### 사용 예\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 개발\n\n### CI/CD 및 보안\n\n* ![적용 범위](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n* ![테스트](https://img.shields.io/badge/tests-15%20passed-green.svg)\n* ![주름 옷깃](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### GitHub Actions의 체크\n\n| 유형 | 도구 | 설명 |\n| --- | ---------- | ----------- |\n| 린팅 | 주름 옷깃 | 코드 포맷팅 및 분석 |\n| 테스트 | 파이테스트 | 단위 및 통합 테스트 |\n| 코팅 | pytest-cov | 코드 커버리지 보고서 |\n\n#### 보안 및 비밀\n\n1. 토큰 보호:\n\n * `.env` 에서 `.gitignore` 로\n * CI/CD를 위한 GitHub의 비밀\n * 속도 제한: 100개 요청/15분\n\n2. 비밀 설정:\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### 기여하다\n\n1. 저장소를 포크하세요\n\n2. 종속성 설치: `uv pip install -e \".[dev]\"`\n\n3. 브랜치를 생성합니다: `git checkout -b feature/name`\n\n4. 변경 사항을 확인하세요:\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. 풀 리퀘스트 만들기\n\n## 📫 지원\n\n* GitHub 이슈: [이슈 생성](https://github.com/rbctmz/mcp-server-strava/issues)\n* 텔레그램: [@greg\\_kisel](https://t.me/greg_kisel)\n\n## 📄 라이센스\n\n[MIT](LICENSE)","Korean","ko-KR",{"_39":70,"_43":73,"_48":74},{"_41":71,"_43":44,"_45":72},"Integration Strava API с Model Context Protocol SDK","# Интеграция Strava API с Model Context Protocol (MCP) SDK\n\n![CI](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)\n![Codecov](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)\n![Python](https://img.shields.io/badge/python-3.10+-blue.svg)\n![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)\n![Ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\nИнтеграция для анализа тренировок и получения рекомендаций на основе данных Strava с использованием Model Context Protocol SDK.\n\n## 🚀 Возможности\n\n- Анализ тренировок из Strava\n- Рекомендации по тренировкам\n- Автоматическое обновление токенов\n- Rate limiting для API запросов\n\n## 📋 Требования\n\n- Python 3.10+\n- [Claude Desktop](https://claude.ai/desktop)\n- [Strava](https://www.strava.com) аккаунт\n- [uv](https://github.com/astral-sh/uv) (рекомендуется)\n\n## ⚙️ Установка\n\n```bash\n# Клонируем репозиторий\ngit clone https://github.com/rbctmz/mcp-server-strava.git\ncd mcp-server-strava\n\n# Установка через uv (рекомендуется)\ncurl -LsSf https://astral.sh/uv/install.sh | sh\nuv pip install .\n\n# Установка в режиме разработки\nuv pip install -e \".[dev]\"\n```\n\n### Установка MCP SDK\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 Настройка\n\n### Настройка Strava API\n\n1. Перейдите на [страницу настроек API](https://www.strava.com/settings/api)\n2. Создайте приложение:\n - Application Name: MCP Strava Integration\n - Category: Training Analysis\n - Website: \n - Authorization Callback Domain: localhost\n\n### Настройка окружения\n\n1. Создайте файл с переменными окружения:\n\n ```bash\n cp .env-template .env\n ```\n\n2. Получите токены доступа:\n\n ```bash\n python scripts/auth.py\n ```\n\n3. Проверьте настройку:\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 API и примеры\n\n### Ресурсы и инструменты\n\n| Тип | Название | Описание |\n|-----|----------|----------|\n| Ресурс | `strava://activities` | Список активностей |\n| Ресурс | `strava://activities/{id}` | Детали активности |\n| Ресурс | `strava://athlete/zones` | Тренировочные зоны |\n| Ресурс | `strava://athlete/clubs` | Клубы атлета |\n| Ресурс | `strava://gear/{gear_id}` | Информация о снаряжении |\n| Инструмент | `analyze_activity(activity_id)` | Анализ тренировки |\n| Инструмент | `analyze_training_load(activities)` | Анализ нагрузки |\n| Инструмент | `get_activity_recommendations()` | Рекомендации |\n\n### Примеры использования\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 Разработка\n\n### CI/CD и безопасность\n\n- ![Coverage](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n- ![Tests](https://img.shields.io/badge/tests-15%20passed-green.svg)\n- ![Ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### Проверки в GitHub Actions\n\n| Тип | Инструмент | Описание |\n|-----|------------|-----------|\n| Линтинг | ruff | Форматирование и анализ кода |\n| Тесты | pytest | Unit и интеграционные тесты |\n| Покрытие | pytest-cov | Отчет о покрытии кода |\n\n#### Безопасность и секреты\n\n1. Защита токенов:\n - `.env` в `.gitignore`\n - GitHub Secrets для CI/CD\n - Rate limiting: 100 запросов/15 мин\n\n2. Настройка секретов:\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### Contributing\n\n1. Форкните репозиторий\n2. Установите зависимости: `uv pip install -e \".[dev]\"`\n3. Создайте ветку: `git checkout -b feature/name`\n4. Проверьте изменения:\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. Создайте Pull Request\n\n## 📫 Поддержка\n\n- GitHub Issues: [создать issue](https://github.com/rbctmz/mcp-server-strava/issues)\n- Telegram: [@greg_kisel](https://t.me/greg_kisel)\n\n## 📄 Лицензия\n\n[MIT](LICENSE)\n","Russian","ru-RU",{"_39":76,"_43":80,"_48":81},{"_41":77,"_43":78,"_45":79},"Strava API 与模型上下文协议 SDK 的集成","mcp-服务器-strava","# Strava API 与模型上下文协议 (MCP) SDK 集成\n\n![CI](https://github.com/rbctmz/mcp-server-strava/actions/workflows/ci.yml/badge.svg)![编解码器](https://codecov.io/gh/rbctmz/mcp-server-strava/branch/main/graph/badge.svg)![Python](https://img.shields.io/badge/python-3.10+-blue.svg)![许可证：MIT](https://img.shields.io/badge/License-MIT-yellow.svg)![拉夫](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n使用模型上下文协议 SDK 集成基于 Strava 数据的训练分析和建议。\n\n## 🚀 功能\n\n* Strava 锻炼分析\n* 培训建议\n* 自动令牌更新\n* API 请求的速率限制\n\n## 📋 要求\n\n* Python 3.10+\n* [克劳德桌面](https://claude.ai/desktop)\n* [Strava](https://www.strava.com)帐户\n* [紫外线](https://github.com/astral-sh/uv)（推荐）\n\n## ⚙️ 安装\n\n```bash\n# Клонируем репозиторий\ngit clone https://github.com/rbctmz/mcp-server-strava.git\ncd mcp-server-strava\n\n# Установка через uv (рекомендуется)\ncurl -LsSf https://astral.sh/uv/install.sh | sh\nuv pip install .\n\n# Установка в режиме разработки\nuv pip install -e \".[dev]\"\n```\n\n### 安装 MCP SDK\n\n```bash\nuv add \"mcp[cli]\"\n```\n\n## 🔧 设置\n\n### 设置 Strava API\n\n1. 前往[API 设置页面](https://www.strava.com/settings/api)\n2. 创建应用程序：\n * 应用程序名称：MCP Strava Integration\n * 类别：训练分析\n * 网站： \n * 授权回调域：localhost\n\n### 设置环境\n\n1. 创建包含环境变量的文件：\n\n ```bash\n cp .env-template .env\n ```\n\n2. 获取访问令牌：\n\n ```bash\n python scripts/auth.py\n ```\n\n3. 检查设置：\n\n ```bash\n mcp dev src/server.py\n curl -X GET \"http://localhost:8000/activities\"\n ```\n\n## 📚 API 和示例\n\n### 资源和工具\n\n| 类型 | 姓名 | 描述 |\n| -- | ----------------------------------- | ------ |\n| 资源 | `strava://activities` | 活动列表 |\n| 资源 | `strava://activities/{id}` | 活动详情 |\n| 资源 | `strava://athlete/zones` | 训练区 |\n| 资源 | `strava://athlete/clubs` | 运动员俱乐部 |\n| 资源 | `strava://gear/{gear_id}` | 设备信息 |\n| 工具 | `analyze_activity(activity_id)` | 训练分析 |\n| 工具 | `analyze_training_load(activities)` | 负载分析 |\n| 工具 | `get_activity_recommendations()` | 建议 |\n\n### 使用示例\n\n```python\nfrom mcp import ClientSession\n\n# Получение активностей\nasync with ClientSession() as session:\n activities = await session.read_resource(\"strava://activities\")\n activity = await session.read_resource(\"strava://activities/12345678\")\n\n# Анализ тренировки\nresult = analyze_activity(activity_id=\"12345678\")\n\"\"\"\n{\n \"type\": \"Run\",\n \"distance\": 5000,\n \"moving_time\": 1800,\n \"analysis\": {\n \"pace\": 5.5, # мин/км\n \"effort\": \"Средняя\"\n }\n}\n\"\"\"\n\n# Анализ нагрузки\nsummary = analyze_training_load(activities)\n\"\"\"\n{\n \"activities_count\": 10,\n \"total_distance\": 50.5, # км\n \"total_time\": 5.2, # часы\n \"heart_rate_zones\": {\n \"easy\": 4, # ЧСС < 120\n \"medium\": 4, # ЧСС 120-150\n \"hard\": 2 # ЧСС > 150\n }\n}\n\"\"\"\n\n# Получение тренировочных зон\nasync with ClientSession() as session:\n zones = await session.read_resource(\"strava://athlete/zones\")\n \"\"\"\n {\n \"heart_rate\": {\n \"custom_zones\": true,\n \"zones\": [\n {\"min\": 0, \"max\": 120, \"name\": \"Z1 - Recovery\"},\n {\"min\": 120, \"max\": 150, \"name\": \"Z2 - Endurance\"},\n {\"min\": 150, \"max\": 170, \"name\": \"Z3 - Tempo\"},\n {\"min\": 170, \"max\": 185, \"name\": \"Z4 - Threshold\"},\n {\"min\": 185, \"max\": -1, \"name\": \"Z5 - Anaerobic\"}\n ]\n },\n \"power\": {\n \"zones\": [\n {\"min\": 0, \"max\": 180},\n {\"min\": 181, \"max\": 250},\n {\"min\": 251, \"max\": 300},\n {\"min\": 301, \"max\": 350},\n {\"min\": 351, \"max\": -1}\n ]\n }\n }\n \"\"\"\n```\n\n## 🛠 开发\n\n### CI/CD 和安全\n\n* ![覆盖范围](https://img.shields.io/badge/coverage-72%25-yellow.svg)\n* ![测试](https://img.shields.io/badge/tests-15%20passed-green.svg)\n* ![拉夫](https://img.shields.io/badge/code%20style-ruff-000000.svg)\n\n#### GitHub Actions 中的检查\n\n| 类型 | 工具 | 描述 |\n| ---- | ---------- | -------- |\n| 代码检查 | 皱领 | 代码格式化和分析 |\n| 测试 | pytest | 单元和集成测试 |\n| 涂层 | pytest-cov | 代码覆盖率报告 |\n\n#### 安全和秘密\n\n1. 代币保护：\n\n * `.env`到`.gitignore`\n * GitHub 的 CI/CD 秘诀\n * 速率限制：100 个请求/15 分钟\n\n2. 设置秘密：\n\n ```bash\n # В GitHub: Settings → Secrets → Actions\n STRAVA_CLIENT_ID=\n STRAVA_CLIENT_SECRET=\n STRAVA_REFRESH_TOKEN=\n ```\n\n### 贡献\n\n1. 分叉存储库\n\n2. 安装依赖项： `uv pip install -e \".[dev]\"`\n\n3. 创建分支： `git checkout -b feature/name`\n\n4. 检查更改：\n\n ```bash\n ruff format .\n ruff check .\n pytest --cov=src\n ```\n\n5. 创建拉取请求\n\n## 📫 支持\n\n* GitHub 问题：[创建问题](https://github.com/rbctmz/mcp-server-strava/issues)\n* 电报： [@greg\\_kisel](https://t.me/greg_kisel)\n\n## 📄 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