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Codebase Insight

Analyze your codebases for patterns and best practices. Manage architecture decisions and generate documentation effortlessly. Enhance your development workflow with intelligent insights and AI-assisted debugging.

Installation

Installing for Claude Desktop

Option 1: One-Command Installation

npx mcpbar@latest install tosin2013/mcp-codebase-insight -c claude

This command will automatically install and configure the Codebase Insight MCP server for your selected client.

Option 2: Manual Configuration

Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

After opening your configuration file, copy and paste this configuration:

View JSON configuration
{
  "mcpServers": {
    "Codebase Insight": {
      "command": "npx",
      "args": [
        "-y",
        "vite-react-typescript-starter"
      ],
      "env": {}
    }
  }
}

MCP Codebase Insight - WIP

🚧 Development in Progress

This project is actively under development. Features and documentation are being continuously updated.

Overview

MCP Codebase Insight is a system for analyzing and understanding codebases through semantic analysis, pattern detection, and documentation management.

Current Development Status

Completed Features

  • ✅ Core Vector Store System
  • ✅ Basic Knowledge Base
  • ✅ SSE Integration
  • ✅ Testing Framework
  • ✅ TDD and Debugging Framework (rules_template integration)

In Progress

  • 🔄 Documentation Management System
  • 🔄 Advanced Pattern Detection
  • 🔄 Performance Optimization
  • 🔄 Integration Testing
  • 🔄 Debugging Utilities Enhancement

Planned

  • 📋 Extended API Documentation
  • 📋 Custom Pattern Plugins
  • 📋 Advanced Caching Strategies
  • 📋 Deployment Guides
  • 📋 Comprehensive Error Tracking System

Quick Start

  1. Installation

    pip install mcp-codebase-insight
    
  2. Basic Usage

    from mcp_codebase_insight import CodebaseAnalyzer
    
    analyzer = CodebaseAnalyzer()
    results = analyzer.analyze_code("path/to/code")
    
  3. Running Tests

    # Run all tests
    pytest tests/
    
    # Run unit tests
    pytest tests/unit/
    
    # Run component tests
    pytest tests/components/
    
    # Run tests with coverage
    pytest tests/ --cov=src --cov-report=term-missing
    
  4. Debugging Utilities

    from mcp_codebase_insight.utils.debug_utils import debug_trace, DebugContext, get_error_tracker
    
    # Use debug trace decorator
    @debug_trace
    def my_function():
        # Implementation
    
    # Use debug context
    with DebugContext("operation_name"):
        # Code to debug
    
    # Track errors
    try:
        # Risky operation
    except Exception as e:
        error_id = get_error_tracker().record_error(e, context={"operation": "description"})
        print(f"Error recorded with ID: {error_id}")
    

Testing and Debugging

Test-Driven Development

This project follows Test-Driven Development (TDD) principles:

  1. Write a failing test first (Red)
  2. Write minimal code to make the test pass (Green)
  3. Refactor for clean code while keeping tests passing (Refactor)

Our TDD documentation can be found in docs/tdd/workflow.md.

Debugging Framework

We use Agans' 9 Rules of Debugging:

  1. Understand the System
  2. Make It Fail
  3. Quit Thinking and Look
  4. Divide and Conquer
  5. Change One Thing at a Time
  6. Keep an Audit Trail
  7. Check the Plug
  8. Get a Fresh View
  9. If You Didn't Fix It, It Isn't Fixed

Learn more about our debugging approach in docs/debuggers/agans_9_rules.md.

Documentation

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

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