206 lines
10 KiB
HTML
206 lines
10 KiB
HTML
<!DOCTYPE html>
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<html lang="de">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Strava MCP Server | Modern Training Data Access</title>
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<link rel="stylesheet" href="style.css">
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</head>
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<body>
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<div class="bg-gradient"></div>
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<div class="container">
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<nav>
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<div class="logo">STRAVA<span>MCP</span></div>
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<ul class="nav-links">
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<li><a href="#features" data-i18n="nav-features">Features</a></li>
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<li><a href="#architecture" data-i18n="nav-arch">Architecture</a></li>
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<li><a href="#installation" data-i18n="nav-install">Installation</a></li>
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<li><a href="https://git.hnrx.net/hnrx/strava-mcp-server" data-i18n="nav-repo">GitHub</a></li>
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</ul>
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<div class="lang-switch">
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<button class="lang-btn active" onclick="setLanguage('en')">EN</button>
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<button class="lang-btn" onclick="setLanguage('de')">DE</button>
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</div>
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</nav>
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<header class="hero">
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<img src="assets/hero.png" alt="Futuristic Background" class="hero-img">
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<h1 data-i18n="hero-title">Empower your AI with Strava Data.</h1>
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<p data-i18n="hero-subtitle">A production-ready Model Context Protocol (MCP) server that exposes the Strava
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API for AI agents and LLMs.</p>
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<div class="btn-group">
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<a href="https://git.hnrx.net/hnrx/strava-mcp-server" class="btn btn-primary" data-i18n="btn-start">Get
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Started</a>
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<a href="#architecture" class="btn btn-secondary" data-i18n="btn-more">Learn More</a>
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</div>
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</header>
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<section id="features">
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<div class="section-title">
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<h2 data-i18n="features-title">Features</h2>
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<p data-i18n="features-subtitle">Comprehensive access to your training data through standardized MCP
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tools.</p>
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</div>
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<div class="grid">
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<div class="card">
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<span class="card-icon">👤</span>
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<h3 data-i18n="feat-1-t">Athlete Profiles</h3>
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<p data-i18n="feat-1-d">Detailed profiles, heart rate zones, and power stats for personalized
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analysis.</p>
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</div>
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<div class="card">
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<span class="card-icon">🚴</span>
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<h3 data-i18n="feat-2-t">Activity Deep-Dive</h3>
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<p data-i18n="feat-2-d">Access laps, streams, comments, and detailed segment efforts.</p>
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</div>
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<div class="card">
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<span class="card-icon">📍</span>
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<h3 data-i18n="feat-3-t">Segments & Routes</h3>
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<p data-i18n="feat-3-d">Explore popular segments and your saved routes with all metadata.</p>
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</div>
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<div class="card">
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<span class="card-icon">⚙️</span>
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<h3 data-i18n="feat-4-t">Hardware Tracking</h3>
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<p data-i18n="feat-4-d">Manage your equipment and track the mileage of your bikes and shoes.</p>
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</div>
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</div>
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</section>
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<section id="architecture" class="architecture">
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<div>
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<h2 data-i18n="arch-title">Dual-Output Architecture</h2>
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<p data-i18n="arch-p">Optimized for both humans and machines. Every tool delivers two outputs:</p>
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<br>
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<ul style="list-style: none; color: var(--text-dim);">
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<li style="margin-bottom: 1rem;"><strong style="color: var(--primary);" data-i18n="arch-user-t">User
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Content:</strong> <span data-i18n="arch-user-d">Formatted markdown for an aesthetic display
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in the chat.</span></li>
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<li><strong style="color: #fff;" data-i18n="arch-llm-t">Assistant Resource:</strong> <span
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data-i18n="arch-llm-d">Structured JSON for precise data processing by the LLM.</span></li>
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</ul>
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</div>
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<div class="code-window">
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<div class="code-header">
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<div class="dot red"></div>
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<div class="dot yellow"></div>
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<div class="dot green"></div>
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</div>
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<div class="code-content">
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<pre>
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<span class="comment">// JSON Resource for Assistant</span>
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{
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<span class="keyword">"id"</span>: <span class="string">"12345678"</span>,
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<span class="keyword">"name"</span>: <span class="string">"Morning Ride"</span>,
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<span class="keyword">"distance"</span>: <span class="string">"45200"</span>,
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<span class="keyword">"moving_time"</span>: <span class="string">"5400"</span>,
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<span class="keyword">"audience"</span>: [<span class="string">"assistant"</span>]
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}</pre>
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</div>
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</div>
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</section>
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<section id="installation" class="quick-start">
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<h2 data-i18n="install-title">Quick Start</h2>
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<p data-i18n="install-p">Start the server locally with a single command via UV.</p>
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<div class="terminal">
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<span>$</span> uv run strava-mcp-server
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</div>
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</section>
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<footer>
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<p>© 2024 Strava MCP Server. Build for high-performance AI Agents.</p>
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</footer>
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</div>
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<script>
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const translations = {
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en: {
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"nav-features": "Features",
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"nav-arch": "Architecture",
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"nav-install": "Installation",
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"nav-repo": "Source",
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"hero-title": "Empower your AI with Strava Data.",
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"hero-subtitle": "A production-ready Model Context Protocol (MCP) server that exposes the Strava API for AI agents and LLMs.",
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"btn-start": "Get Started",
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"btn-more": "Learn More",
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"features-title": "Features",
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"features-subtitle": "Comprehensive access to your training data through standardized MCP tools.",
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"feat-1-t": "Athlete Profiles",
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"feat-1-d": "Detailed profiles, heart rate zones, and power stats for personalized analysis.",
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"feat-2-t": "Activity Deep-Dive",
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"feat-2-d": "Access laps, streams, comments, and detailed segment efforts.",
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"feat-3-t": "Segments & Routes",
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"feat-3-d": "Explore popular segments and your saved routes with all metadata.",
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"feat-4-t": "Hardware Tracking",
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"feat-4-d": "Manage your equipment and track the mileage of your bikes and shoes.",
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"arch-title": "Dual-Output Architecture",
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"arch-p": "Optimized for both humans and machines. Every tool delivers two outputs:",
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"arch-user-t": "User Content:",
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"arch-user-d": "Formatted markdown for an aesthetic display in the chat.",
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"arch-llm-t": "Assistant Resource:",
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"arch-llm-d": "Structured JSON for precise data processing by the LLM.",
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"install-title": "Quick Start",
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"install-p": "Start the server locally with a single command via UV."
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},
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de: {
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"nav-features": "Funktionen",
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"nav-arch": "Architektur",
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"nav-install": "Installation",
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"nav-repo": "Quellcode",
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"hero-title": "Analysiere deine Strava-Daten mit KI-Power.",
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"hero-subtitle": "Ein produktionsreifer Model Context Protocol (MCP) Server, der die Strava API für AI Agents und LLMs nutzbar macht.",
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"btn-start": "Loslegen",
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"btn-more": "Mehr erfahren",
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"features-title": "Funktionen",
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"features-subtitle": "Umfangreicher Zugriff auf deine Trainingsdaten über standardisierte MCP Tools.",
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"feat-1-t": "Athleten-Profile",
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"feat-1-d": "Detaillierte Profile, Herzfrequenz-Zonen und Power-Stats für personalisierte Analysen.",
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"feat-2-t": "Aktivitäts-Analyse",
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"feat-2-d": "Zugriff auf Laps, Streams, Kommentare und detaillierte Segment-Efforts.",
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"feat-3-t": "Segmente & Routen",
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"feat-3-d": "Erkunde beliebte Segmente und deine gespeicherten Routen mit allen Metadaten.",
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"feat-4-t": "Hardware-Tracking",
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"feat-4-d": "Verwalte deine Ausrüstung und verfolge die Laufleistung deiner Bikes und Schuhe.",
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"arch-title": "Dual-Output Architektur",
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"arch-p": "Optimiert für Mensch und Maschine. Jedes Tool liefert zwei Ausgaben:",
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"arch-user-t": "User Content:",
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"arch-user-d": "Formatiertes Markdown für eine ästhetische Anzeige im Chat.",
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"arch-llm-t": "Assistant Resource:",
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"arch-llm-d": "Strukturiertes JSON für präzise Datenverarbeitung durch das LLM.",
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"install-title": "Schnellstart",
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"install-p": "Starte den Server lokal mit nur einem Befehl über UV."
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}
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};
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function setLanguage(lang) {
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localStorage.setItem('preferredLang', lang);
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// Update all text elements
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document.querySelectorAll('[data-i18n]').forEach(el => {
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const key = el.getAttribute('data-i18n');
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if (translations[lang][key]) {
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el.textContent = translations[lang][key];
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}
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});
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// Update toggle buttons
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document.querySelectorAll('.lang-btn').forEach(btn => {
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btn.classList.remove('active');
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if (btn.textContent.toLowerCase() === lang) {
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btn.classList.add('active');
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}
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});
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document.documentElement.lang = lang;
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}
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// Initialize from storage or browser language
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const savedLang = localStorage.getItem('preferredLang') || (navigator.language.startsWith('de') ? 'de' : 'en');
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setLanguage(savedLang);
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</script>
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</body>
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</html> |