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Workout MCP Server

@ipdelete

Repository

Basic information

Category

Other

Transports

stdio

Author

ipdelete

About Workout MCP Server

MCP Server for workout info

#workout#fitness#analytics

Workout MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "workout_mcp_server": {
      "command": "python",
      "args": [
        "-m",
        "workout_mcp_server"
      ]
    }
  }
}

Workout MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Workout MCP Server?

A Model Context Protocol (MCP) server that provides cycling workout analytics tools, enabling LLMs to analyze fitness data, calculate training metrics, and provide insights into athletic performance.

How to use Workout MCP Server?

Install via uvx workout_mcp_server (recommended) or pip install workout_mcp_server and run with python -m workout_mcp_server. Configure with Claude Desktop or VS Code MCP Client by adding the server configuration to the appropriate JSON file. Use the provided tools to retrieve workouts and compute fitness, fatigue, and form scores.

Key features of Workout MCP Server

  • Retrieves workout history (last 50 or last 7 workouts)
  • Looks up specific workouts by unique ID
  • Computes CTL (Fitness) via 42-day weighted average of TSS
  • Computes ATL (Fatigue) via 7-day weighted average of TSS
  • Computes TSB (Form) as difference between fitness and fatigue
  • Provides structured workout data including TSS, power, distance, and type

Use cases of Workout MCP Server

  • Analyze training load and recovery status for cyclists
  • Provide insights on workout history and performance trends
  • Assist athletes in planning training cycles based on metrics
  • Enable AI assistants to answer fitness-related queries

Frequently asked questions

1

What fitness metrics does the server compute?

It computes CTL (Fitness), ATL (Fatigue), and TSB (Form) using exponentially weighted moving averages of Training Stress Score (TSS).

2

How do I install and run the server?

Use `uvx workout_mcp_server` with uv (no installation needed) or run `pip install workout_mcp_server` then `python -m workout_mcp_server`.

3

What data does a workout contain?

Each workout includes id, date, duration_minutes, distance_km, avg_power_watts, tss, and workout_type. The dataset is built-in (50 workouts).

4

How do I configure it with Claude Desktop?

Add the appropriate JSON block to your `claude_desktop_config.json` under `mcpServers`, using either `uvx` or `python -m` depending on your installation method.

5

Are there any dependencies or runtime requirements?

Python is required; uv is optional but recommended. No external data source or authentication is needed—workouts come from a built-in dataset.

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