Overview of Code2Flow MCP Server

The Code2Flow MCP Server is an innovative tool that revolutionizes the way developers and AI applications interact with source code. By encapsulating the code2flow command-line tool within an MCP (Model Context Protocol) server, it provides a standardized method for generating and accessing code call graphs. This integration is a game-changer for AI applications, allowing them to seamlessly interact with codebases across multiple programming languages, including Python, JavaScript, Ruby, and PHP.

Key Features

Multi-Language Support

The Code2Flow MCP Server supports a wide range of programming languages, making it a versatile tool for developers working in diverse coding environments. This feature ensures that regardless of the language used, developers can generate accurate and insightful call graphs.

MCP Protocol Integration

By utilizing the MCP protocol, the server offers a standardized approach to accessing and generating code call graphs. This protocol ensures compatibility and ease of integration with AI applications, allowing for a more streamlined workflow.

PNG Image Output

The server outputs call graphs in PNG format, providing a clear and visually appealing representation of code interactions. This feature is particularly useful for developers and AI applications that require a visual understanding of code structures.

Version Checking and Complexity Analysis

Beyond generating call graphs, the server offers additional tools such as version checking and code complexity analysis. These features provide developers with deeper insights into their codebases, helping them identify potential areas for optimization and improvement.

Use Cases

AI Application Integration

The Code2Flow MCP Server is ideal for AI applications that need to interact with codebases. By providing a standardized protocol for generating call graphs, AI applications can better understand and manipulate code, leading to more intelligent and context-aware operations.

Developer Productivity

For developers, the server offers a powerful tool for understanding complex codebases. By generating visual call graphs, developers can quickly identify relationships and dependencies within their code, facilitating faster debugging and optimization.

Codebase Analysis

The server’s complexity analysis feature provides valuable insights into the maintainability and efficiency of a codebase. This information is crucial for developers looking to improve code quality and performance.

UBOS Platform Integration

The UBOS platform is a full-stack AI agent development platform that aims to bring AI agents to every business department. By integrating the Code2Flow MCP Server, UBOS enhances its ability to orchestrate AI agents and connect them with enterprise data. This integration allows businesses to build custom AI agents with their LLM models and multi-agent systems, further enhancing their operational efficiency and decision-making capabilities.

Installation Requirements

• Python 3.7+
• Windows 11 or other supported operating systems
• PowerShell or other command-line terminals
• Installed code2flow command-line tool

Installation Steps

1. Clone the repository:

   git clone https://github.com/kursk-ye/code2flow-mcp-server.git
   cd code2flow-mcp-server
   

2. Create and activate a virtual environment (recommended):

   python -m venv venv
   .venvScriptsActivate.ps1  # In PowerShell
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Install the code2flow command-line tool:

   pip install code2flow
   

Usage

Running Directly with Python

1. Start the MCP server:

   python server.py
   

Using MCP Tools

1. Use the MCP Inspector tool:

   mcp dev server.py
   

2. Install to Claude Desktop:

   mcp install server.py
   

3. Add to Cursor MCP configuration:

   "code2flow": {
     "command": "cmd",
     "args": [
       "/c",
       "python",
       "path/to/server.py"
     ]
   }
   

Available Tools and Resources

The server offers several MCP tools and resources, including generating call graphs, checking code2flow versions, and analyzing code complexity. These tools provide developers with a comprehensive suite for code analysis and optimization.

Conclusion

The Code2Flow MCP Server is an invaluable asset for developers and AI applications alike. By providing a standardized, multi-language tool for generating and analyzing code call graphs, it enhances productivity, code quality, and AI integration. With its seamless integration into the UBOS platform, businesses can leverage this technology to build smarter, more efficient AI agents.