token-efficient-mcp-template

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This skill should be used when creating token-efficient hook systems and MCP server architectures for web applications. Use for React/FastAPI, Django, Node.js projects that need smart caching, progressive context loading, and 95%+ token reduction. Essential for projects requiring monitoring, debugging, data analysis, and system health tools.

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When & Why to Use This Skill

This Claude skill provides a comprehensive framework for building token-efficient MCP (Model Context Protocol) servers and sophisticated hook systems. It is designed to transform web applications into high-performance AI ecosystems, achieving over 95% token reduction through intelligent caching, progressive context loading, and differential analysis. Ideal for developers using React, FastAPI, Django, or Node.js, it optimizes how LLMs interact with system tools and data while significantly lowering operational costs.

Use Cases

  • Case 1: Reducing API costs in production AI agents by implementing smart caching and 95%+ token reduction strategies.
  • Case 2: Building scalable MCP servers for real-time system monitoring, log analysis, and database health tracking across microservices.
  • Case 3: Implementing progressive context loading to allow AI agents to process large codebases or datasets without hitting context window limits.
  • Case 4: Creating secure, sandboxed hook systems for web applications to validate tool parameters and provide real-time guidance to AI models.
nametoken-efficient-mcp-template
descriptionThis skill should be used when creating token-efficient hook systems and MCP server architectures for web applications. Use for React/FastAPI, Django, Node.js projects that need smart caching, progressive context loading, and 95%+ token reduction. Essential for projects requiring monitoring, debugging, data analysis, and system health tools.

Token-Efficient MCP & Hook System Template

Overview

Transform any web application into a token-efficient ecosystem with smart MCP server tools and sophisticated hook systems. Provides 95%+ token reduction through intelligent caching, progressive context loading, and optimized tool discovery patterns.

Quick Start

Initialize new project ecosystem:

# Run the initialization script
python scripts/init_template.py --project-type {react|fastapi|django|node} --name my-project

Generate specific components:

  • Hook system: python scripts/generate_hooks.py --type {pre-tool|context|session}
  • MCP server: python scripts/setup_mcp_server.py --categories {logs,system,database}
  • Caching: python scripts/configure_caching.py --strategy {smart|progressive|differential}

Core Capabilities

1. Hook System Generation

Create sophisticated hook systems that provide real-time tool guidance and token efficiency nudges.

Pre-Tool-Use Hooks:

  • Analyze tool usage patterns before execution
  • Suggest token-efficient alternatives (95-99% savings)
  • Validate tool parameters and security constraints
  • Provide context-aware recommendations

Context Injection Hooks:

  • Progressive context loading (summary → targeted → full)
  • Session state management and tracking
  • Dependency resolution and caching
  • Background refresh mechanisms

Session Management Hooks:

  • Timeout protection and resource limits
  • Background task coordination
  • Health monitoring and validation
  • Graceful error handling and recovery

2. MCP Server Architecture

Bootstrap production-ready MCP servers with modular tool categories and intelligent caching.

Tool Categories:

  • logs: Error pattern analysis, log aggregation, troubleshooting
  • system: Health monitoring, performance metrics, status checks
  • database: Query optimization, connection management, backup verification
  • performance: Real-time monitoring, resource tracking, bottleneck detection
  • execution: Sandboxed code execution, data transformation, analysis
  • optimization: Token efficiency, cache management, progressive disclosure

Built-in Features:

  • Smart caching with configurable TTLs
  • Progressive disclosure patterns
  • Background refresh strategies
  • Token usage optimization
  • Security sandboxing

3. Token Efficiency Framework

Implement proven patterns for dramatic token reduction without sacrificing functionality.

Smart Caching Strategies:

  • Differential analysis (99% token reduction)
  • Context-aware summarization
  • Intelligent cache invalidation
  • Background refresh for stale data

Progressive Context Loading:

  • Summary mode (150 tokens)
  • Targeted mode (800 tokens)
  • Full context (complete file/data)
  • Automatic level selection based on user intent

Optimization Patterns:

  • Query result aggregation
  • Batch processing for multiple operations
  • Compression of repetitive data
  • Smart prefetching based on usage patterns

Project Templates

React/FastAPI Template

python scripts/init_template.py --project-type react-fastapi --name my-app
  • Frontend-backend tool integration
  • WebSocket real-time updates
  • API endpoint monitoring
  • Component-level performance tracking

Django Analytics Template

python scripts/init_template.py --project-type django-analytics --name dashboard
  • Database query optimization
  • Admin panel integration
  • User activity tracking
  • Report generation tools

Node.js Microservices Template

python scripts/init_template.py --project-type node-microservices --name services
  • Service health monitoring
  • Inter-service communication tracking
  • Load balancing metrics
  • Distributed tracing tools

Resources

scripts/

Executable automation scripts for template generation and project setup.

Core Scripts:

  • init_template.py - Initialize complete project ecosystem
  • generate_hooks.py - Generate hook system components
  • setup_mcp_server.py - Create MCP server with tool categories
  • configure_caching.py - Set up token efficiency strategies
  • health_check.py - Validate system connectivity and health

Usage Example:

# Initialize React/FastAPI project with full ecosystem
python scripts/init_template.py \
  --project-type react-fastapi \
  --name my-ecommerce-app \
  --include-mcp-server \
  --include-hooks \
  --caching-strategy smart

references/

Comprehensive documentation and implementation guides.

Key References:

  • hook_patterns.md - Hook implementation best practices and patterns
  • mcp_design_guide.md - MCP server architecture and design principles
  • token_optimization.md - Caching strategies and token efficiency techniques
  • security_guide.md - Sandbox configurations and security best practices
  • integration_examples.md - Detailed integration examples for different stacks

Reference Usage:

  • Load specific references when implementing custom components
  • Consult design guides for architectural decisions
  • Use examples as templates for project-specific customizations

assets/

Template files and configurations for different project types.

Template Categories:

  • hook_templates/ - Hook system templates for different environments
  • mcp_templates/ - MCP server tool definitions and schemas
  • config_templates/ - YAML configurations for different stacks
  • docker_templates/ - Container configurations and deployment scripts

Asset Usage:

  • Copy templates directly to new projects
  • Customize configurations for specific requirements
  • Use as starting points for custom implementations

Implementation Workflow

Phase 1: Project Analysis

  1. Identify project type and requirements
  2. Determine needed tool categories
  3. Select caching and optimization strategies
  4. Configure security and performance parameters

Phase 2: Template Generation

  1. Run initialization script with project parameters
  2. Generate hook system components
  3. Set up MCP server with selected tools
  4. Configure caching and optimization strategies

Phase 3: Customization

  1. Adapt templates to project-specific needs
  2. Configure tool parameters and security settings
  3. Set up monitoring and health checks
  4. Test integration and validate functionality

Phase 4: Deployment

  1. Configure deployment environments
  2. Set up monitoring and alerting
  3. Validate performance and token efficiency
  4. Document customizations and usage patterns

Best Practices

Token Efficiency:

  • Always use progressive context loading for large files
  • Implement smart caching with appropriate TTLs
  • Use differential analysis for change detection
  • Batch operations when possible

Security:

  • Configure sandboxing for code execution
  • Implement proper authentication and authorization
  • Use environment-specific configurations
  • Regular security audits and updates

Performance:

  • Monitor token usage and optimize patterns
  • Use background refresh for stale data
  • Implement proper error handling and recovery
  • Regular performance validation and tuning

This skill transforms the sophisticated patterns from production systems into reusable templates, enabling any developer to create token-efficient tool ecosystems with minimal effort and maximum impact.