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    Code Analysis Mcp

    21 stars
    Python
    Updated Oct 1, 2025

    Table of Contents

    • ✨ Highlights
    • Limitations
    • 🚀 Quick Start
    • 💡 Example Usage
    • 🔧 Available Tools
    • initialize_repository
    • get_repo_info
    • get_repo_structure
    • read_file
    • ⚙️ Technical Details
    • 📝 License

    Table of Contents

    • ✨ Highlights
    • Limitations
    • 🚀 Quick Start
    • 💡 Example Usage
    • 🔧 Available Tools
    • initialize_repository
    • get_repo_info
    • get_repo_structure
    • read_file
    • ⚙️ Technical Details
    • 📝 License

    Documentation

    Code Analysis MCP Server

    A Model Context Protocol (MCP) server that enables AI models to understand and analyze codebases through natural language conversations.

    ✨ Highlights

    • Natural Code Exploration: Ask high-level questions about your codebase
    code
    "What are all the different payment providers integrated in the system?"
    • Deep Code Understanding: Extract insights about data models and system architecture
    code
    "How does the user authentication flow work from frontend to database?"
    • Dynamic Analysis: Trace data flows and understand system relationships
    code
    "Show me all the places where we calculate transaction fees"

    Limitations

    This tool is a simpler alternative to more sophisticated code analysis tools / copilot like Aider. While it lacks the advanced code analysis capabilities and robustness of tools like Aider, it offers a lightweight solution for codebase exploration if you already have a Claude Pro subscription. The main advantages are:

    • Cost-Effective: Using your existing Claude Pro subscription means no additional API costs, unlike tools that can get expensive when analyzing large codebases
    • Simple Setup: Quick to get started with minimal configuration
    • Basic Analysis: Good for high-level code understanding and exploration

    Note that due to its simpler approach to code analysis, it may make more errors or provide less detailed insights compared to more specialized tools.

    🚀 Quick Start

    1. Install the server:

    bash
    git clone https://github.com/saiprashanths/code-analysis-mcp.git
    cd code-analysis-mcp

    2. Install Claude Desktop App. For more instructions on setting up an MCP Server with Claude Desktop app, see docs

    3. Configure the server in Claude Desktop's configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
    json
    {
      "mcpServers": {
        "code-analysis": {
          "command": "uv",
          "args": [
            "--directory",
            "/PATH/TO/YOUR/REPO",
            "run",
            "code_analysis.py"
          ]
        }
      }
    }

    4. Restart Claude Desktop and start analyzing your code!

    5. Ensure the tool is correctly setup

    • Clicking the tools icon should display the code-analysis tools
    • Clicking the integrations button should display the analyze_code_repository prompt

    💡 Example Usage

    Here's how you might use the tool to understand a complex codebase:

    Start by clicking on the analyze_code_repository prompt shown below. That will guide you through the process

    to initialize the repo and get started.

    text
    You: How does the transaction processing work in this system?
    
    Claude: Let me analyze the data flow for transactions. 
    Looking at the codebase, I can see that transaction processing happens through several key components:
    
    1. Raw transaction data is captured in the `TransactionEvent` model with fields for:
       - Payment status
       - Amount
       - Fee calculations
       - Processing timestamps
    
    2. This data is then processed through the PaymentSummary model, which:
       - Validates payment provider responses
       - Calculates processing fees
       - Records transaction status
    
    Would you like me to explain any part of this in more detail?
    
    You: What are the key database tables involved?
    
    Claude: The main tables in the transaction processing pipeline are:
    
    1. transaction_events: Stores raw payment events
    2. payment_summary: Processed transaction records
    3. payment_providers: Provider configuration
    4. merchant_accounts: Account-specific settings
    
    Let me know if you'd like to see the schema for any of these tables!

    🔧 Available Tools

    initialize_repository

    Initialize a code repository for analysis:

    python
    initialize_repository("/path/to/repo")
    # Output: Successfully initialized code repository at: /path/to/repo

    get_repo_info

    Retrieve information about the initialized repository:

    python
    get_repo_info()
    # Output:
    # Code Repository Information:
    # Path: /path/to/repo
    # Exists: True
    # Is Directory: True
    # Found .gitignore file

    get_repo_structure

    Examine repository file structure:

    python
    get_repo_structure(depth=2)
    # Output:
    # 📁 src/
    #   📁 api/
    #     📄 routes.py
    #     📄 models.py
    #   📁 utils/
    #     📄 helpers.py
    #   📄 main.py

    read_file

    Read and analyze specific files:

    python
    read_file("src/api/models.py")
    # Output:
    # File: src/api/models.py
    # Language: python
    # Size: 2.3 KB
    # 
    # [File contents...]

    ⚙️ Technical Details

    • Default scanning depth: 3 levels
    • Maximum file size: 1MB
    • Maximum lines per file: 1000
    • Ignores paths listed in .gitignore
    • Local file system access only
    • Validates file paths to prevent directory traversal

    📝 License

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

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