this is a MCP server that create uml text based class diagrams, project tree structure and a list of modules anf functions in the project to assist cursor in understanding the project.
Documentation
MCP Docs Tools
A Node.js-based MCP (Model Context Protocol) tool server that provides three focused documentation generation tools for Python projects. Built as an npm package that can be installed directly from the Git repository.
Features
🔧 Three Powerful Tools
1. **create_class_diagram** - Analyzes Python files and generates UML class diagrams in PlantUML format
2. **create_tree_structure** - Creates clean directory tree structure documentation with smart exclusions
3. **create_module_functions** - Documents module-level functions with signatures, decorators, and type hints
🚀 Key Benefits
- Zero Configuration: Works out of the box with sensible defaults
- Smart Exclusions: Automatically filters out cache, build, and IDE files
- Rich Documentation: Captures type hints, decorators, docstrings, and inheritance
- MCP Integration: Seamlessly integrates with AI assistants via Model Context Protocol
- Hybrid Architecture: Node.js orchestration + Python AST parsing for reliability
Installation
From Git Repository (Recommended)
# Clone the repository
git clone https://github.com/your-username/mcp-docs-tools.git
cd mcp-docs-tools
# Install dependencies
npm install
# Install globally (optional)
npm install -g .
# Or run directly
npm startDirect Installation from Git
# Install directly from GitHub
npm install -g git+https://github.com/your-username/mcp-docs-tools.git
# Then run
mcp-docs-toolsLocal Development
git clone https://github.com/your-username/mcp-docs-tools.git
cd mcp-docs-tools
npm install
npm startRequirements
- Node.js ≥18.0.0
- Python 3.x (for AST parsing)
- Git (for cloning the repository)
Python Interpreter Detection and Windows Support
The server automatically detects a working Python 3 interpreter at runtime. On Windows it prefers py -3 when available, and falls back to python or python3 if they resolve to Python 3. On macOS/Linux it prefers python3, then falls back to python if it is Python 3.
If no Python 3 interpreter is found, you will see an actionable error:
"Python 3 interpreter not found. Install Python 3 or set MCP_PYTHON (and optional MCP_PYTHON_ARGS). Tried: ..."
Environment Overrides (optional)
You can explicitly specify the interpreter and arguments:
MCP_PYTHON: command or absolute path (e.g.,py,python3,C:\\Python312\\python.exe)MCP_PYTHON_ARGS: space-separated arguments (e.g.,-3)
Examples:
# Windows PowerShell
$env:MCP_PYTHON = "python"
$env:MCP_PYTHON_ARGS = "-3"
npm start# macOS/Linux bash
export MCP_PYTHON=py
export MCP_PYTHON_ARGS=-3
npm startUsage
As MCP Server
Start the server to expose tools via Model Context Protocol:
# If installed globally
mcp-docs-tools
# Or from the project directory
npm start
# Or run directly with node
node bin/server.jsThe server will listen on stdin/stdout and expose three tools that can be called by MCP clients.
Tool Specifications
1. create_class_diagram
Purpose: Generate UML class diagrams from Python code
Parameters:
project_path(string, required): Root path of the Python project to analyze
Output:
- File:
docs/uml.txt - Format: PlantUML syntax
- Content: Classes with public/private methods, attributes, and inheritance relationships
Example:
@startuml
class MyClass {
+public_attr: str
-_private_attr: int
--
+__init__(self, name: str)
+public_method(self, arg: int): bool
-{static} _private_method(): None
}
@enduml2. create_tree_structure
Purpose: Generate project directory tree structure
Parameters:
project_path(string, required): Root path of the project to analyze
Output:
- File:
docs/tree-structure.txt - Format: Unicode box-drawing tree
- Content: Complete file/directory structure with smart exclusions
Example:
my-project
├── src/
│ ├── main.py
│ └── utils/
│ └── helpers.py
├── tests/
│ └── test_main.py
└── README.md3. create_module_functions
Purpose: Document module-level functions and signatures
Parameters:
project_path(string, required): Root path of the Python project to analyze
Output:
- File:
docs/module-functions.txt - Format: Hierarchical markdown documentation
- Content: Functions organized by module with full signatures, decorators, and docstrings
Example:
## Module: src.utils.helpers
### `async def process_data(data: List[str], timeout: int = 30) -> Dict[str, Any]`
**Decorators:**
- `@retry(max_attempts=3)`
**Description:**
Process a list of data items with optional timeout.
**Line:** 42Architecture
Hybrid Node.js + Python Approach
The tool uses a hybrid architecture that combines the best of both worlds:
- Node.js Server: Handles MCP protocol, tool registration, and process orchestration
- Python Scripts: Perform robust AST parsing and documentation generation
- Clean Separation: Protocol handling separate from parsing logic
Project Structure
mcp-docs-tools/
├── package.json # npm package configuration
├── bin/
│ └── server.js # Main MCP server entry point
├── src/
│ ├── server.js # MCP server implementation
│ ├── tools/ # Tool implementations
│ │ ├── class-diagram.js # UML generation wrapper
│ │ ├── tree-structure.js # Tree generation wrapper
│ │ └── module-functions.js # Function docs wrapper
│ └── config/
│ └── exclusions.js # Default exclusion patterns
├── python/
│ ├── generate_uml.py # Python AST parsing for classes
│ ├── generate_tree.py # Directory tree generation
│ ├── generate_functions.py # Function parsing and documentation
│ └── requirements.txt # Python dependencies (none needed)
└── README.mdSmart Exclusions
The tools automatically exclude common files and directories that shouldn't be documented:
Python
__pycache__,*.pyc,*.pyo,*.pydbuild,dist,eggs,*.egg-info- Virtual environments:
venv,.venv,env,virtualenv
Development Tools
- Version control:
.git,.svn,.hg - IDEs:
.idea,.vscode,.cursor - Testing:
.pytest_cache,.coverage,.tox
Build & Package Managers
node_modules,target,out,binpackage-lock.json,yarn.lock,Pipfile.lock
OS & Temporary
.DS_Store,Thumbs.db,*.tmp,*.log
Integration with AI Assistants
Cursor IDE
The configuration depends on how you installed the tools:
Option A: If you cloned the repository (Recommended method)
Create a .cursorrules file in your projects and add this to your Cursor MCP configuration:
{
"mcpServers": {
"docs-tools": {
"command": "node",
"args": ["/path/to/mcp-docs-tools/bin/server.js"],
"cwd": "/path/to/mcp-docs-tools"
}
}
}**Replace /path/to/mcp-docs-tools with the actual path where you cloned the repository.**
For example:
- macOS/Linux:
"/Users/yourname/projects/mcp-docs-tools" - Windows:
"C:\\Users\\yourname\\projects\\mcp-docs-tools"
Option B: If you installed globally with npm install -g
{
"mcpServers": {
"docs-tools": {
"command": "mcp-docs-tools"
}
}
}.cursorrules file content (for any installation method)
Create this .cursorrules file in your Python projects:
# Documentation Tools Integration
## Available MCP Tools
- `create_class_diagram` - Generate UML class diagrams
- `create_tree_structure` - Generate directory tree
- `create_module_functions` - Document module functions
## Usage
Run these tools at session start to generate documentation in `docs/` directory.
Reference the generated files to understand codebase structure.
## Generated Files
- `docs/uml.txt` - PlantUML class diagrams
- `docs/tree-structure.txt` - Directory structure
- `docs/module-functions.txt` - Function documentationClaude Desktop
Option A: If you cloned the repository (Recommended method)
Add to your Claude Desktop MCP configuration:
{
"mcpServers": {
"docs-tools": {
"command": "node",
"args": ["/path/to/mcp-docs-tools/bin/server.js"],
"cwd": "/path/to/mcp-docs-tools"
}
}
}**Replace /path/to/mcp-docs-tools with the actual path where you cloned the repository.**
Option B: If you installed globally with npm install -g
{
"mcpServers": {
"docs-tools": {
"command": "mcp-docs-tools"
}
}
}Quick Setup Guide
1. Clone and install (recommended):
git clone https://github.com/your-username/mcp-docs-tools.git
cd mcp-docs-tools
npm install2. Find your installation path:
pwd
# Copy this path for your MCP configuration3. Update your MCP config with the path from step 2
4. Test the tools in your Python projects!
Error Handling
The tools include comprehensive error handling:
- Python Process Failures: Detailed error messages with stdout/stderr
- Missing Dependencies: Clear instructions for Python installation
- File Permission Issues: Graceful handling with informative messages
- Invalid Project Paths: Path validation before processing
Performance
- Lightweight: Minimal memory footprint with short-lived Python processes
- Fast: Efficient AST parsing with smart file filtering
- Scalable: Handles large codebases with thousands of files
- Concurrent: Multiple tools can run simultaneously
Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request
License
MIT License - see LICENSE file for details.
Support
- Issues: Report bugs and feature requests on GitHub
- Documentation: Full API documentation available in the repository
- Examples: Sample projects and usage patterns in the examples directory
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Made with ❤️ for the Python development community
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