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Performance Optimization

Optimize your MCP servers for better performance and resource usage.

Overview​

Optimizing your MCP servers helps reduce costs, improve response times, and provide better user experience.

Resource Optimization​

Memory Usage​

  • Profile your application
  • Identify memory leaks
  • Use efficient data structures
  • Implement pagination for large datasets

CPU Usage​

  • Use async/await patterns
  • Avoid blocking operations
  • Optimize algorithms
  • Cache expensive computations

Code Optimization​

Efficient Algorithms​

  • Choose appropriate algorithms
  • Avoid unnecessary computations
  • Use built-in functions
  • Optimize data processing

Caching​

Implement caching where appropriate:

  • Cache API responses
  • Cache database queries
  • Cache computed results
  • Set appropriate TTLs

Docker Optimization​

Image Size​

  • Use slim base images
  • Multi-stage builds
  • Remove unnecessary files
  • Leverage layer caching

Build Time​

  • Optimize Dockerfile order
  • Cache dependencies
  • Use .dockerignore
  • Minimize layers

Database Optimization​

If your server uses a database:

  • Use indexes appropriately
  • Optimize queries
  • Use connection pooling
  • Implement query caching

Monitoring​

Monitor performance metrics:

  • Response times
  • Resource usage
  • Error rates
  • Request patterns

Use this data to identify optimization opportunities.

Best Practices​

  1. Profile First: Measure before optimizing
  2. Optimize Hot Paths: Focus on frequently used code
  3. Test Changes: Verify optimizations work
  4. Monitor Impact: Track performance improvements
  5. Iterate: Continuous optimization

Next Steps​