README.md

---
title: Python UML Diagram Generator & MCP Server
emoji: 🐍
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false
license: mit
models:
  - PlantUML
tags:
  - uml
  - python
  - diagrams
  - mcp
  - code-analysis
  - visualization
  - mcp-server-track
short_description: Python UML diagram generator with MCP server support
---

# 🐍 Python UML Diagram Generator & MCP Server

A powerful tool that generates UML class diagrams from Python code with integrated Model Context Protocol (MCP) server functionality for AI assistants.

## 🚀 Features

- **🎨 Interactive Web Interface**: Generate UML class diagrams interactively from Python code
- **🤖 MCP Server Integration**: Works with Claude Desktop, Cursor, and other MCP clients  
- **📊 Advanced Code Analysis**: Enhanced analysis with call graphs, complexity metrics, and function dependencies
- **🔗 Function Call Graphs**: Visualize function relationships and dependencies using pyan3 + graphviz
- **📈 Complexity Metrics**: Cyclomatic complexity, lines of code, parameter analysis
- **⚙️ Standalone Function Analysis**: Perfect for utility scripts with functions (not just classes)
- **🔄 Real-time Processing**: Fast diagram generation using PlantUML
- **💾 Multiple Formats**: PNG images, PlantUML source code, and call graph visualizations
- **🔍 Inheritance Visualization**: Clear parent-child class relationships

## 🎯 Quick Start

1. **Paste Python Code**: Enter your Python code in the text area
2. **Generate Diagram**: Click "Generate Diagram" to create UML visualization
3. **Analyze Structure**: Use "Analyze Code" for detailed code analysis
4. **Download Results**: Save generated diagrams and analysis

## 🤖 MCP Server Integration

This Space automatically serves as an MCP server! To integrate with AI assistants:

### For Claude Desktop (with mcp-remote):
```json
{
  "mcpServers": {
    "python-diagram-generator": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://your-username-space-name.hf.space/gradio_api/mcp/sse",
        "--transport",
        "sse-only"
      ]
    }
  }
}
```

### For Cursor, Cline, and other SSE-compatible clients:
```json
{
  "mcpServers": {
    "python-diagram-generator": {
      "url": "https://your-username-space-name.hf.space/gradio_api/mcp/sse"
    }
  }
}
```

### For Private Spaces:
```json
{
  "mcpServers": {
    "python-diagram-generator": {
      "url": "https://your-username-space-name.hf.space/gradio_api/mcp/sse",
      "headers": {
        "Authorization": "Bearer hf_your_token_here"
      }
    }
  }
}
```

## 🛠️ Available MCP Tools

1. **generate_diagram**: Creates UML class diagrams from Python code
2. **analyze_code_structure**: Provides detailed code structure analysis with enhanced metrics

## 📊 Advanced Analysis Features

### **🔬 Advanced Analysis Tab**
- **Function Call Graphs**: Visual network diagrams showing function dependencies
- **Complexity Analysis**: Cyclomatic complexity scoring for each function
- **Function Metrics**: Lines of code, parameter counts, docstring detection
- **Call Relationship Mapping**: Which functions call which, and call frequency analysis
- **Isolated Function Detection**: Find functions that aren't connected to others
- **Code Quality Recommendations**: Suggestions for refactoring and improvements

### **Enhanced for Standalone Functions**
Perfect for analyzing utility scripts, mathematical functions, data processing pipelines, and other function-heavy code that traditional class-based UML tools miss.

## 💡 Usage Examples

### Example 1: Basic Classes
```python
class Animal:
    def __init__(self, name: str):
        self.name = name
    
    def speak(self) -> str:
        pass

class Dog(Animal):
    def speak(self) -> str:
        return f"{self.name} says Woof!"
```

### Example 2: Complex Inheritance
```python
class Vehicle:
    def __init__(self, brand: str, model: str):
        self.brand = brand
        self.model = model

class Car(Vehicle):
    def __init__(self, brand: str, model: str, doors: int):
        super().__init__(brand, model)
        self.doors = doors
    
    def start_engine(self):
        return "Engine started"

class ElectricCar(Car):
    def __init__(self, brand: str, model: str, doors: int, battery_capacity: float):
        super().__init__(brand, model, doors)
        self.battery_capacity = battery_capacity
    
    def charge(self):
        return "Charging battery"
```

## 🔧 Technical Details

- **Built with**: Gradio 5.33+ with MCP support
- **Analysis Engine**: Python AST + py2puml + pyan3
- **Call Graph Generation**: pyan3 + graphviz for function dependency visualization
- **Diagram Rendering**: PlantUML web service + graphviz DOT rendering
- **Output Formats**: PNG images, PlantUML source code, DOT call graphs
- **MCP Protocol**: Server-Sent Events (SSE) transport
- **Function Analysis**: Cyclomatic complexity, parameter analysis, docstring detection

## 🎨 Features Showcase

- **Real-time Analysis**: Code structure updates as you type
- **Inheritance Detection**: Visualizes parent-child relationships
- **Method & Attribute Mapping**: Complete class member analysis
- **Function Call Graphs**: Interactive network diagrams of function dependencies
- **Complexity Metrics**: Cyclomatic complexity analysis with recommendations
- **Standalone Function Support**: Perfect for utility scripts and mathematical functions
- **Error Handling**: Syntax error detection and reporting
- **Sample Code**: Ready-to-use examples for both classes and functions

## 📱 Compatible MCP Clients

- **Claude Desktop** (via mcp-remote)
- **Cursor IDE**
- **Cline VS Code Extension**
- **Continue VS Code Extension**
- **Custom MCP implementations**

## 🌟 Perfect For

- **Developers**: Understanding code structure and function dependencies quickly
- **Code Reviews**: Visualizing class relationships and call patterns
- **Documentation**: Generating architectural diagrams and function flow charts
- **Education**: Teaching OOP concepts and functional programming patterns
- **Utility Script Analysis**: Understanding standalone function files and mathematical algorithms
- **Refactoring**: Identifying complex functions and isolated code segments
- **AI Assistants**: Enhanced code analysis capabilities with complexity metrics

## 📞 Support & Feedback

- Test with the provided sample code first
- Check the MCP configuration tab for setup instructions
- View API documentation via the "View API" link in the footer

---

**Transform your Python code into beautiful UML diagrams! 🎨✨**