Spotr MCP Server
by thompson-ad
The Spotr MCP server augments Claude with fitness coaching capabilities for the Spotr platform. It acts as a bridge between Claude and the Spotr fitness web application, enabling access to coaching data and storage of generated fitness programs.
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Spotr MCP
A Model Context Protocol (MCP) server designed to augment Claude with fitness coaching capabilities for the Spotr platform.
Overview
SpotrFitnessServer acts as a bridge between Claude and the Spotr fitness web application. It enables Claude to access coaching data and store generated fitness programs in your database.
Features
- Generate personalized fitness programs for clients
- Create program blueprints that can be reused for multiple clients
- Refresh and tweak existing programs
- Analyze client progress and program effectiveness
- Answer questions about programs
Getting Started
Prerequisites
- Node.js
- npm or yarn
- API access to your fitness backend
Installation
# Clone the repository
git clone https://github.com/yourusername/spotr-mcp-server.git
# Install dependencies
cd spotr-mcp-server
npm install
# Set up environment variables
cp .env.example .env
# Edit .env with your API credentials
Running the Server
# Start the server
node server.js
Example Usage
User: "Could you create a strength training program for my client Sarah? She's a 35-year-old intermediate lifter who wants to focus on upper body strength."
Claude: "I've created an 8-week upper body strength program for Sarah and saved it to your Spotr app. The program includes 4 training days per week with a focus on progressive overload for key upper body movements.
You and Sarah can access the full program here: https://app.spotr.coach/programs/123456"
Project Structure
server.js
: Main entry point that sets up the MCP server.env
: Environment variables configurationresources/
: MCP resources for accessing coach and client datatools/
: MCP tools for storing and manipulating programsprompts/
: MCP prompts for program generation and analysis
License
[License information]
Acknowledgments
This project uses the Model Context Protocol developed by Anthropic.