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khaoss85/arvo-mcp

khaoss85/arvo-mcp

📇 ☁️ - Arvo AI workout coach: access training data, workout history, personal records and body progress
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add arvo-mcp -- npx -y arvo-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
3 ★ · khaoss85/arvo-mcp · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 3 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 khaoss85/arvo-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Arvo MCP Server - Fitness & Workout Tracker for Claude

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

> **Fitness tracking MCP server** - Log gym sessions, track personal records (PRs), analyze body progress, and manage training splits through Claude Desktop, Cursor, and other MCP clients.
**arvo-mcp** is a Model Context Protocol (MCP) server that connects your AI assistant to Arvo, an AI-powered fitness coach. Access your **workout history**, **personal records**, **body composition**, and **training plans** directly from Claude Desktop, Cursor, or any MCP-compatible client.
Perfect for fitness enthusiasts who want to:
- 🏋️ Ask "What's my workout today?" and get your personalized training plan
- 📊 Track gym progress with AI-powered insights
- 💪 Monitor PRs, volume, and muscle group distribution
- 📈 Analyze body composition trends over time
Features
- **29 fitness tools** - Profile, workouts, splits, PRs, body progress, and more
- **Read & Write access** - View your data and make changes through natural conversation
- **Secure API key authentication** - Your data stays private
- **Works with any MCP client** - Claude Desktop, Cursor, Windsurf, and more
Quick Start
1. Get your API key
1. Sign up or log in at arvo.guru
2. In the **web app**, open **Settings** → **API Keys** (if you see the simplified settings, switch to **Advanced** mode first — or open https://arvo.guru/settings#api-keys directly)
3. Click **Create Key** and copy your API key
> API-key management is currently web-only and not available in the mobile app.
2. Configure your MCP client
Claude Desktop
Add to your claude_desktop_config.json:
**Config file location:**
- **macOS**: ~/Library/Application Support/Claude/claude_desktop_config.json
- **Windows**: %APPDATA%\Claude\claude_desktop_config.json
Cursor
Add to your Cursor MCP settings:
3. Start chatting!
After restarting your AI client, try asking:
- *"What's my workout for today?"*
- *"Show me my recent PRs"*
- *"How's my progress on bench press?"*
- *"What muscle groups am I training this week?"*
Available Tools
Read-Only Tools (19)
| Tool | Description |
|------|-------------|
| get_user_profile | Get your fitness profile, experience level, and preferences |
| get_active_split | Get your current training split and schedule |
| get_recent_workouts | View your most recent completed workouts |
| get_workout_for_day | Get the workout for any cycle day |
| get_workout_stats | Get aggregated training statistics |
| get_active_insights | View AI-generated training insights |
| get_personal_records | See your PRs for each exercise |
| get_exercise_progress | Track progression for specific exercises |
| get_exercise_video | Get demonstration videos for exercises |
| get_volume_by_muscle | View volume distribution by muscle group |
| get_coach_info | Get your coach's information |
| get_coach_notes | View notes from your coach |
| get_approach_details | Learn about your training methodology |
| get_body_progress | Track body composition changes |
| get_cycle_history | View training cycle history |
| get_booking_info | See your PT session bookings |
| get_ai_memory | Access saved AI context about you |
| get_caloric_history | View caloric phase history |
| get_approach_history | See methodology changes over time |
Write Tools (10)
| Tool | Description |
|------|-------------|
| save_memory | Save notes for the AI to remember |
来源
awesome · https://github.com/khaoss85/arvo-mcp
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