# khaoss85/arvo-mcp [Health: Active]

**Category:** 🏃 Sports  
**Repository:** https://github.com/khaoss85/arvo-mcp  
**GitHub Stars:** 3  
**npm Downloads (last month):** 120  
**Views:** 3  
**Installs:** 0  
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**Directory Page:** https://allmcps.com/mcp/khaoss85-arvo-mcp

## Description
AI workout coach MCP server for Arvo. Access training data, workout history, personal records, body progress, and 29 fitness tools through Claude Desktop.

## Tools
Capabilities this server exposes over MCP:

- **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
- **save_memory** — Save notes for the AI to remember
- **update_caloric_phase** — Change your current bulk/cut/maintain phase
- **update_weak_points** — Update priority muscle groups
- **report_physical_issue** — Log pain or injuries
- **skip_exercise** — Skip an exercise in today's workout
- **generate_workout** — Generate a new workout
- **update_equipment** — Update your available equipment
- **add_exercise** — Add an exercise to your workout
- **swap_exercise** — Request exercise alternatives
- **apply_swap** — Apply an exercise swap

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `npx` (confidence: high):

```json
"mcpServers": {
  "arvo-mcp": {
    "command": "npx",
    "args": ["-y","arvo-mcp"],
    "env": {
      "ARVO_API_KEY": ""
    }
  }
}
```

**Requires environment variables:** `ARVO_API_KEY` — the values above are empty placeholders; fill in real credentials before running (see the repository for what each one is for).

## Documentation

## What khaoss85/arvo-mcp MCP server does

The khaoss85/arvo-mcp MCP server exposes Arvo fitness data and actions to AI clients that support the Model Context Protocol. It is intended for people using Arvo as an AI workout coach and want to ask questions about their training or make supported changes without switching applications.

The server includes 29 tools split between read-only and write operations. Read operations cover the user profile, training split, completed workouts, scheduled workouts, aggregated statistics, AI insights, personal records, exercise progression, exercise videos, muscle-group volume, coach details and notes, training methodology, body progress, cycle history, PT bookings, saved AI memory, caloric phases, and methodology history.

Write operations can save AI memory, change a caloric phase, update priority muscle groups, report pain or injuries, skip an exercise, generate a workout, update available equipment, add an exercise, request exercise alternatives, and apply a swap.

## How it works

The khaoss85/arvo-mcp MCP server uses the standard MCP stdio transport. A compatible client starts the local Node.js process and communicates with it through MCP. The process then contacts Arvo's cloud service to retrieve or update the account data associated with the supplied API key.

Access is controlled by an Arvo API key. Arvo keys can use read-only or read-write scopes, so the selected key determines whether the client can only inspect data or also perform supported changes. The repository states that communication uses HTTPS and that the local API key is not sent to third parties.

## Setup and configuration

Install and run the khaoss85/arvo-mcp MCP server with Node.js 18 or newer through the published npm package:

```json
{
  "command": "npx",
  "args": ["-y", "arvo-mcp"],
  "env": {
    "ARVO_API_KEY": "your Arvo API key"
  }
}
```

Add this configuration to an MCP client such as Claude Desktop or Cursor, then restart the client. The README also identifies Windsurf and other MCP-compatible clients as supported. Create the API key from an Arvo account under Settings and API Keys. An Arvo account is required.

`ARVO_API_KEY` is required. `ARVO_BASE_URL` is optional and defaults to `https://arvo.guru`; it can be used when a different API base URL is needed. The server requires an internet connection because it fetches data from Arvo's cloud service.

## Tools and capabilities

Typical read requests include asking for today's workout, reviewing recent PRs, checking bench-press progression, inspecting weekly muscle-group volume, or viewing body-composition changes. The tools also expose coach notes, training methodology details, bookings, and saved context for the AI.

Supported changes include modifying the current bulk, cut, or maintenance phase; updating equipment and weak points; recording a physical issue; and changing exercises in a workout. These operations can affect Arvo account data, so a read-write key should be used only when those changes are intended.

## Limitations and notes

The khaoss85/arvo-mcp MCP server is not an offline tracker. Although its MCP process runs locally, it needs network access to communicate with Arvo. It also depends on an Arvo account and API key, and its available data is limited to what Arvo exposes through the listed tools and the permissions assigned to the key.

The repository documents Claude Desktop, Cursor, and Windsurf compatibility, along with standard MCP-client compatibility. It does not describe a separate web interface or local database for this server. The project is licensed under MIT.

_Full upstream README: https://allmcps.com/mcp/khaoss85-arvo-mcp/readme_