Personal MCP Server

from typing import Dict, List from mcp.server.fastmcp import FastMCP def register_prompts(mcp: FastMCP) -> None: """Register MCP prompts.""" @mcp.prompt() def analyze_workout_load(workout_history: str) -> List[Dict]: """Analyze workout load and suggest adjustments.""" return [ { "role": "user", "content": { "type": "text", "text": f"""Please analyze my workout history and suggest adjustments based on: 1. Shoulder rehabilitation status 2. Recent performance 3. Recovery patterns 4. Energy levels and mood from journal entries Workout History: {workout_history} Particularly focus on: - Safe progression for shoulder exercises - Maintaining leg strength - Volume management - Recovery metrics""", }, } ] @mcp.prompt() def nutrition_recommendations(nutrition_log: str, start_date: str, end_date: str) -> List[Dict]: """Get personalized nutrition recommendations.""" return [ { "role": "user", "content": { "type": "text", "text": ( # Use parentheses for line continuation f"""Based on my meal logs for period {start_date} to {end_date}, please provide: Nutrition Log: {nutrition_log} 1. Protein intake optimization 2. Meal timing suggestions 3. Pre/post workout nutrition 4. Supplement timing (creatine, vitamins, omega-3) 5. Patterns between nutrition and energy/mood 6. Hunger and satisfaction patterns""" ), }, } ] @mcp.prompt() def journal_insights(entries: str) -> List[Dict]: """Generate insights from journal entries.""" return [ { "role": "user", "content": { "type": "text", "text": f"""Please analyze my journal entries and provide insights on: Entries: {entries} 1. Patterns in mood and energy levels 2. Sleep quality trends and correlations 3. Stress management effectiveness 4. Relationship between workouts and well-being 5. Impact of nutrition on daily metrics 6. Progress towards goals mentioned in entries 7. Suggestions for improvement based on patterns""", }, } ]