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Summarization Functions

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An MCP server for intelligent text summarization, configurable with various AI providers.

๐Ÿ”ฅ๐Ÿ”ฅ๐Ÿ”ฅโœ“ VerifiedAccount requiredNeeds API keys

Summarization Functions

Intelligent text summarization for the Model Context Protocol

Features โ€ข AI Agent Integration โ€ข Installation โ€ข Usage

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Overview

A powerful MCP server that provides intelligent summarization capabilities through a clean, extensible architecture. Built with modern TypeScript and designed for seamless integration with AI workflows.

AI Agent Integration

This MCP server was primarily developed to enhance the performance and reliability of AI agents like Roo Cline and Cline. It addresses a critical challenge in AI agent operations: context window management.

Context Window Optimization

AI agents frequently encounter situations where their context window gets rapidly filled with large outputs from:

  • Command execution results
  • File content readings
  • Directory listings
  • API responses
  • Error messages and stack traces

This server helps maintain efficient context usage by:

  1. Providing concise, relevant summaries instead of full content
  2. Storing full content for reference when needed
  3. Offering focused analysis based on specific needs (security, API surface, etc.)
  4. Supporting multiple output formats for optimal context utilization

Benefits for AI Agents

  • Reduced Failure Rates: By preventing context window overflow
  • Improved Response Quality: Through focused, relevant summaries
  • Enhanced Efficiency: By maintaining important context while reducing noise
  • Better Resource Management: Through intelligent content caching and retrieval
  • Flexible Integration: Supporting multiple AI providers and configuration options

When integrating with AI agents, include the following in your agent's instructions:

# CONTEXT MANAGEMENT

You have access to summarization functions through the MCP server. These functions are NOT optional - you MUST use them for ALL potentially large outputs to prevent context overflow:

MANDATORY SUMMARIZATION:
- You MUST ALWAYS use summarization functions for:
    - ANY first time file reading operations (unless you are CERTAIN its small and you are going to edit it)
    - ALL command execution outputs
    - EVERY directory analysis
    - ANY API responses or error logs
    - ANY output that could be large

NEVER attempt to process raw output directly - ALWAYS use the appropriate summarization function:
โ€ข For commands: summarize_command
โ€ข For files: summarize_files
โ€ข For directories: summarize_directory
โ€ข For other text: summarize_text

ALWAYS utilize available features:
โ€ข Specify hints for focused analysis
โ€ข Choose appropriate output formats
โ€ข Use content IDs to access full details only when absolutely necessary

There is NO NEED to process perfect or complete output. Summarized content is ALWAYS preferred over raw data. When in doubt, use summarization.

Summarization in action on the Ollama repository (Gemini 2.0 Flash summarization, Claude 3.5 agent)

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Features

  • Command Output Summarization
    Execute commands and get concise summaries of their output

  • File Content Analysis
    Summarize single or multiple files while maintaining technical accuracy

  • Directory Structure Understanding
    Get clear overviews of complex directory structures

  • Flexible Model Support Use models from different providers

  • AI Agent Context Optimization Prevent context window overflow and improve AI agent performance through intelligent summarization