MCP-exercise-analyzer

# ISMAR MCP: Medical Context Pose Analyzer A Model Context Protocol (MCP) server for analyzing 3D vector joint data to detect and provide feedback on yoga poses, exercise form, and posture. ## Overview This project provides a medical context analyzer for 3D vector joints that: - Detects and tracks body postures and joint positions - Analyzes yoga poses against ideal reference poses - Provides feedback on pose accuracy and suggested corrections - Generates comprehensive session reports with medical insights - Calculates calories burned and exercise benefits ## Features - **Real-time Pose Analysis**: Compares user poses against ideal reference poses - **Medical Context**: Offers insights on health benefits and potential risks - **Exercise Tracking**: Monitors pose transitions, pace, and exercise quality - **Comprehensive Reports**: Generates detailed session summaries with metrics ## Prerequisites - Node.js (v14 or higher) - npm or yarn ## Installation 1. Clone the repository: ```bash git clone https://github.com/your-username/ismar-mcp.git cd ismar-mcp ``` 2. Install dependencies: ```bash npm install ``` 3. Build the project: ```bash npm run build ``` ## Usage ### Running the MCP Server The server implements the Model Context Protocol and runs over standard I/O: ```bash node build/index.js ``` Alternatively, use the binary directly if it's installed globally: ```bash yoga-analyzer ``` ### Available Tools The MCP server provides the following tools: 1. **list-frames**: Lists available yoga pose frames with pagination 2. **read-frame**: Reads a specific yoga pose frame by URI 3. **generate-session-report**: Generates a comprehensive report analyzing the yoga session ### Data Files The server requires the following data files: - `ideal_poses.json`: Contains reference poses for various yoga positions - `yoga_medical_info.json`: Medical information about each pose, benefits, and calorie burn rates - `current_frames.json`: Current session frame data captured from the user ## Integration This MCP server can be integrated with any MCP-compatible client, including: - VR/AR applications - Fitness tracking systems - Telemedicine platforms - Health monitoring applications ## Development ### Project Structure - `src/index.ts`: Main server implementation - `src/types.d.ts`: Type definitions - `src/ideal_poses.json`: Reference pose data - `src/yoga_medical_info.json`: Medical context information - `src/current_frames.json`: Current session frame data ### Building from Source ```bash npm run build ``` This will generate the built files in the `build` directory. ## License ISC License ## Dependencies - `@modelcontextprotocol/sdk`: Model Context Protocol SDK - `zod`: Schema validation library - TypeScript development environment