MCP Code Indexer

The MCP Code Indexer is an intelligent code retrieval tool designed specifically for large AI language models. It improves the efficiency and accuracy of code processing through semantic understanding and vectorized indexing, supporting functions such as code analysis, quality assessment, and dependency management.

Developer tools Search tools #Code Retrieval #Semantic Analysis #AI Assistance #Code Optimization .Python

rating : 2.5 points

downloads : 16

update time : 2025-04-23

What is the MCP Code Indexer?

The MCP Code Indexer is a tool designed specifically for large AI language models. It helps the models better analyze and retrieve code libraries through semantic understanding. It supports functions such as cross - language code search, code structure analysis, and similar code detection.

How to use the MCP Code Indexer?

Users can easily install and configure the MCP Code Indexer. They can complete code indexing, searching, and analysis through simple commands. It supports various application scenarios, such as code navigation, quality assessment, and dependency management.

Applicable Scenarios

It is suitable for individual developers, team collaborations, and enterprise - level projects, helping to quickly find code, optimize code quality, and manage project dependencies.

Main Features

Intelligent Code RetrievalSemantic - based code search that not only matches keywords but also understands the actual meaning of the code.

Cross - Language Code RetrievalSupports code search in multiple programming languages with a unified interface for easy use.

Code Structure AnalysisAutomatically parses classes, functions, and dependency relationships in the code.

Code Quality AssessmentProvides code quality scores and improvement suggestions.

Document and Comment ExtractionExtracts comments and documentation information from the code to assist in generating technical documents.

Similar Code DetectionDetects duplicate logic or similar code fragments.

Code Metrics StatisticsCounts indicators such as the number of code lines and complexity.

Project Dependency AnalysisVisually displays the project's dependency relationships.

Advantages and Limitations

Advantages

Improve the efficiency of code understanding and analysis

Support multi - language code retrieval

Reduce repetitive work and improve development efficiency

Limitations

Indexing very large code libraries may take more time

Requires certain hardware resource support

How to Use

Install Dependencies

Run pip to install the required dependency packages.

Install the Tool

Execute the setup script to complete the installation.

Configure the Server

Edit the configuration file to specify the server path and parameters.

Usage Examples

Example 1: Search for Code SnippetsAfter the user enters keywords, the system returns matching code snippets.

Example 2: Analyze Code QualityAnalyze code quality and provide optimization suggestions.

Frequently Asked Questions

How to start using the MCP Code Indexer?

Does it support multiple programming languages?

How to improve the accuracy of code search?

Related Resources

Project Homepage

Visit the GitHub project homepage for more information.

User Manual

Download the user manual to understand the detailed usage instructions.

Demo Video

Watch the demo video to understand the functions of the MCP Code Indexer.

🚀 MCP Code Indexer

An intelligent code retrieval tool based on the Model Context Protocol (MCP), providing efficient and accurate code library retrieval capabilities for large AI language models.

English Version

🚀 Quick Start

The MCP Code Indexer is a code retrieval tool designed specifically for large AI language models. Through vectorized indexing and semantic understanding, it helps AI better understand and analyze code libraries, significantly improving the efficiency and accuracy of code-related tasks.

Project Address: https://github.com/zxfgds/mcp-code-indexer

✨ Features

Intelligent Code Retrieval

Semantic-based code search: Understands the meaning of code rather than just keyword matching.
Cross-language code retrieval: Supports code search across different programming languages.
Intelligent code snippet extraction: Automatically identifies the complete code context.

Code Analysis Capabilities

Code structure analysis: Analyzes classes, functions, and dependency relationships.
Code quality assessment: Evaluates the quality of code.
Documentation and comment extraction: Extracts documentation and comments from code.
Similar code detection: Detects similar code snippets.
Code metric statistics: Calculates code metrics.
Project dependency analysis: Analyzes project dependencies.

Optimized Context Processing

Intelligent Token consumption control: Reduces unnecessary context information.
Structured code context provision: Provides structured code context.
Multi-project parallel indexing and retrieval: Supports parallel indexing and retrieval of multiple projects.
Persistent project identification: Avoids repeated indexing.

Full MCP Protocol Support

Compliance with MCP data interaction specifications: Meets the MCP data interaction standards.
Rich toolset provision: Provides a rich set of tools.
Asynchronous operation and progress feedback: Supports asynchronous operations and provides progress feedback.

📚 Documentation

Application Scenarios

Claude Desktop Application

Enhanced code understanding: Helps Claude understand the user's code library more accurately and provide more precise suggestions and answers.
Intelligent code navigation: Quickly locates relevant code snippets and improves the efficiency of Q&A.
Code quality improvement: Provides more professional code optimization suggestions through code analysis functions.
Project dependency management: Helps understand and manage project dependencies.
Documentation generation assistance: Assists in generating technical documentation based on code comments and structure analysis.

VSCode Extension

Real-time code analysis: Obtains code analysis results directly in the editor.
Intelligent code recommendation: Provides more accurate code suggestions based on project context.
Refactoring assistance: Identifies code patterns that can be optimized and assists in code refactoring.
Dependency relationship visualization: Intuitively displays code dependencies.
Team collaboration enhancement: Helps team members better understand the code library.

📦 Installation

Install Dependencies

pip install -r requirements.txt

Install the Tool

python setup.py install

Configuration Instructions

Claude Desktop Configuration

Open Claude Desktop and go to the plugin marketplace to install the MCP Code Indexer.
Select "MCP Code Indexer" in the plugin settings and complete the configuration as prompted.

VSCode Configuration

Open Visual Studio Code.
Go to the Extensions marketplace, search for "MCP Code Indexer" and install it.
After installation, find the MCP-related options in the Settings and configure them.

💻 Usage Examples

Basic Usage

Right-click on a selected code snippet in the code editor and select "MCP Code Indexer" for retrieval or analysis.

Advanced Usage

Enter mcp-indexer:<command> in the command palette to perform specific tasks, such as indexing projects and analyzing dependencies.

Project Value

Improve efficiency: Reduce repetitive work and increase development speed.
Optimize resources: Make reasonable use of computing resources and reduce Token consumption.
Enhance collaboration: Promote team code review and knowledge sharing.
Ensure quality: Ensure code maintainability and reliability through automated analysis.